Miracle-dz/UniFAR-FTUs huggingface dataset:
Pembrolizumab for Early Triple-Negative Breast Cancer.

BACKGROUND Previous trials showed promising antitumor activity and an acceptable safety profile associated with pembrolizumab in patients with early triple-negative breast cancer. Whether the addition of pembrolizumab to neoadjuvant chemotherapy would significantly increase the percentage of patients with early triple-negative breast cancer who have a pathological complete response (defined as no invasive cancer in the breast and negative nodes) at definitive surgery is unclear. METHODS In this phase 3 trial, we randomly assigned (in a 2:1 ratio) patients with previously untreated stage II or stage III triple-negative breast cancer to receive neoadjuvant therapy with four cycles of pembrolizumab (at a dose of 200 mg) every 3 weeks plus paclitaxel and carboplatin (784 patients; the pembrolizumab-chemotherapy group) or placebo every 3 weeks plus paclitaxel and carboplatin (390 patients; the placebo-chemotherapy group); the two groups then received an additional four cycles of pembrolizumab or placebo, and both groups received doxorubicin-cyclophosphamide or epirubicin-cyclophosphamide. After definitive surgery, the patients received adjuvant pembrolizumab or placebo every 3 weeks for up to nine cycles. The primary end points were a pathological complete response at the time of definitive surgery and event-free survival in the intention-to-treat population. RESULTS At the first interim analysis, among the first 602 patients who underwent randomization, the percentage of patients with a pathological complete response was 64.8% (95% confidence interval [CI], 59.9 to 69.5) in the pembrolizumab-chemotherapy group and 51.2% (95% CI, 44.1 to 58.3) in the placebo-chemotherapy group (estimated treatment difference, 13.6 percentage points; 95% CI, 5.4 to 21.8; P<0.001). After a median follow-up of 15.5 months (range, 2.7 to 25.0), 58 of 784 patients (7.4%) in the pembrolizumab-chemotherapy group and 46 of 390 patients (11.8%) in the placebo-chemotherapy group had disease progression that precluded definitive surgery, had local or distant recurrence or a second primary tumor, or died from any cause (hazard ratio, 0.63; 95% CI, 0.43 to 0.93). Across all treatment phases, the incidence of treatment-related adverse events of grade 3 or higher was 78.0% in the pembrolizumab-chemotherapy group and 73.0% in the placebo-chemotherapy group, including death in 0.4% (3 patients) and 0.3% (1 patient), respectively. CONCLUSIONS Among patients with early triple-negative breast cancer, the percentage with a pathological complete response was significantly higher among those who received pembrolizumab plus neoadjuvant chemotherapy than among those who received placebo plus neoadjuvant chemotherapy. (Funded by Merck Sharp & Dohme [a subsidiary of Merck]; KEYNOTE-522 ClinicalTrials.gov number, NCT03036488.).
Augmenting Vacuolar H+-ATPase Function Prevents Cardiomyocytes from Lipid-Overload Induced Dysfunction

The diabetic heart is characterized by a shift in substrate utilization from glucose to lipids, which may ultimately lead to contractile dysfunction. This substrate shift is facilitated by increased translocation of lipid transporter CD36 (SR-B2) from endosomes to the sarcolemma resulting in increased lipid uptake. We previously showed that endosomal retention of CD36 is dependent on the proper functioning of vacuolar H+-ATPase (v-ATPase). Excess lipids trigger CD36 translocation through inhibition of v-ATPase function. Conversely, in yeast, glucose availability is known to enhance v-ATPase function, allowing us to hypothesize that glucose availability, via v-ATPase, may internalize CD36 and restore contractile function in lipid-overloaded cardiomyocytes. Increased glucose availability was achieved through (a) high glucose (25 mM) addition to the culture medium or (b) adenoviral overexpression of protein kinase-D1 (a kinase mediating GLUT4 translocation). In HL-1 cardiomyocytes, adult rat and human cardiomyocytes cultured under high-lipid conditions, each treatment stimulated v-ATPase re-assembly, endosomal acidification, endosomal CD36 retention and prevented myocellular lipid accumulation. Additionally, these treatments preserved insulin-stimulated GLUT4 translocation and glucose uptake as well as contractile force. The present findings reveal v-ATPase functions as a key regulator of cardiomyocyte substrate preference and as a novel potential treatment approach for the diabetic heart.
MYC’s Fine Line Between B Cell Development and Malignancy

The transcription factor MYC is transiently expressed during B lymphocyte development, and its correct modulation is essential in defined developmental transitions. Although temporary downregulation of MYC is essential at specific points, basal levels of expression are maintained, and its protein levels are not completely silenced until the B cell becomes fully differentiated into a plasma cell or a memory B cell. MYC has been described as a proto-oncogene that is closely involved in many cancers, including leukemia and lymphoma. Aberrant expression of MYC protein in these hematological malignancies results in an uncontrolled rate of proliferation and, thereby, a blockade of the differentiation process. MYC is not activated by mutations in the coding sequence, and, as reviewed here, its overexpression in leukemia and lymphoma is mainly caused by gene amplification, chromosomal translocations, and aberrant regulation of its transcription. This review provides a thorough overview of the role of MYC in the developmental steps of B cells, and of how it performs its essential function in an oncogenic context, highlighting the importance of appropriate MYC regulation circuitry.
Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs and pathways

Discovering driver pathways is an essential step to uncover the molecular mechanism underlying cancer and to explore precise treatments for cancer patients. However, due to the difficulties of mapping genes to pathways and the limited knowledge about pathway interactions, most previous work focus on identifying individual pathways. In practice, two (or even more) pathways interplay and often cooperatively trigger cancer. In this study, we proposed a new approach called CDPathway to discover cooperative driver pathways. First, CDPathway introduces a driver impact quantification function to quantify the driver weight of each gene. CDPathway assumes that genes with larger weights contribute more to the occurrence of the target disease and identifies them as candidate driver genes. Next, it constructs a heterogeneous network composed of genes, miRNAs and pathways nodes based on the known intra(inter)-relations between them and assigns the quantified driver weights to gene-pathway and gene-miRNA relational edges. To transfer driver impacts of genes to pathway interaction pairs, CDPathway collaboratively factorizes the weighted adjacency matrices of the heterogeneous network to explore the latent relations between genes, miRNAs and pathways. After this, it reconstructs the pathway interaction network and identifies the pathway pairs with maximal interactive and driver weights as cooperative driver pathways. Experimental results on the breast, uterine corpus endometrial carcinoma and ovarian cancer data from The Cancer Genome Atlas show that CDPathway can effectively identify candidate driver genes [area under the receiver operating characteristic curve (AUROC) of $\geq $0.9] and reconstruct the pathway interaction network (AUROC of>0.9), and it uncovers much more known (potential) driver genes than other competitive methods. In addition, CDPathway identifies 150% more driver pathways and 60% more potential cooperative driver pathways than the competing methods. The code of CDPathway is available at http://mlda.swu. edu.cn/codes.php? name=CDPathway.
Glycoprotein 5 Is Cleaved by Cathepsin E during Porcine Reproductive and Respiratory Syndrome Virus Membrane Fusion

PRRS, caused by PRRSV, is an economically critical factor in pig farming worldwide. As PRRSV is a lipid membrane-wrapped virus, merging of the PRRSV envelope with the host cell membrane is indispensable for viral infection. However, there is a lack of knowledge on its membrane fusion. Here, we first explored when and where PRRSV membrane fusion occurs. Furthermore, we determined which host cell factors were involved in the process. Importantly, PRRSV GP5 is shown to be cleaved by cathepsin E during membrane fusion. Our work not only provides information on PRRSV membrane fusion for the first time but also deepens our understanding of the molecular mechanisms of PRRSV infection, which provides a foundation for future applications in the prevention and control of PRRS. ABSTRACT Porcine reproductive and respiratory syndrome (PRRS) is a serious viral disease affecting the global swine industry. Its causative agent, PRRS virus (PRRSV), is an enveloped virus, and therefore membrane fusion between its envelope and host cell target membrane is critical for viral infection. Though much research has focused on PRRSV infection, the detailed mechanisms involved in its membrane fusion remain to be elucidated. In the present study, we performed confocal microscopy in combination with a constitutively active (CA) or dominant negative (DN) mutant, specific inhibitors, and small interfering RNAs (siRNAs), as well as multiple other approaches, to explore PRRSV membrane fusion. We first observed that PRRSV membrane fusion occurred in Rab11-recycling endosomes during early infection using labeled virions and subcellular markers. We further demonstrated that low pH and cathepsin E in Rab11-recycling endosomes are critical for PRRSV membrane fusion. Moreover, PRRSV glycoprotein 5 (GP5) is identified as being cleaved by cathepsin E during this process. Taken together, our findings provide in-depth information regarding PRRSV pathogenesis, which support a novel basis for the development of antiviral drugs and vaccines. IMPORTANCE PRRS, caused by PRRSV, is an economically critical factor in pig farming worldwide. As PRRSV is a lipid membrane-wrapped virus, merging of the PRRSV envelope with the host cell membrane is indispensable for viral infection. However, there is a lack of knowledge on its membrane fusion. Here, we first explored when and where PRRSV membrane fusion occurs. Furthermore, we determined which host cell factors were involved in the process. Importantly, PRRSV GP5 is shown to be cleaved by cathepsin E during membrane fusion. Our work not only provides information on PRRSV membrane fusion for the first time but also deepens our understanding of the molecular mechanisms of PRRSV infection, which provides a foundation for future applications in the prevention and control of PRRS.
How Selective Are Real Wage Cuts?

Using linked employer–employee panel data for Germany, this paper investigates whether firms implement real wage reductions in a selective manner. In line with insider– outsider and several strands of efficiency wage theory, we find strong evidence for selective wage cuts with high-productivity workers being spared even when controlling for permanent differences in firms’ wage policies. In contrast to some recent contributions stressing fairness considerations, we also find that wage cuts increase wage dispersion among peers rather than narrowing it. Notably, the same selectivity pattern shows up when restricting our analysis to firms covered by collective agreements or having a works council. JEL classification: J30, J31
A Bilinear Multi-Scale Convolutional Neural Network for Fine-grained Object Classification

 Abstract —Coarse-grained object classification with simple backgrounds has become quite mature, but the fine-grained object classification task against complex backgrounds is still challenging because there are only subtle differences in the local areas between different classes of fine-grained objects. In this paper, we propose a novel multi-scale convolutional neural network (msCNN) architecture that used for fine-grained object classification, which can extract discriminate local features at different scales in pyramid scale space. And a simplified bilinear model is used to carry out the end-to-end training for object classification. In the training phase, we design a distributed learning method with sample penalty term based on the sample distribution to optimize the network, which can improve the generalization ability of the network. In addition, we avoid using costly manual annotations like bounding box throughout the training and classification process. Finally, we present extensive experiments and visualizations on CUB-200-2011 dataset and ILSVRC2012_Dog dataset that analyze the effects of the bilinear msCNN model on the fine-grained object classification task. The classification accuracy shows that the significant improvement of our msCNN model on the fine-grained object classification.
SERUM INTERLEUKIN-18 AS A NOVEL BIOMARKER FOR DISEASE ACTIVITY OF SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS

Interleukin-18 (IL-18) is a vital cytokine, which mediated organ failure and elevated in autoimmune disorders as Systemic Lupus Erythematosus. This study investigated the importance role of IL-18 as a diagnostic marker for disease activity of systemic lupus erythematosus (SLE) and development of lupus nephritis (LN). This cross-sectional study was carried out on 41 SLE patients with LN, 31 lupus non-nephritis patients and 20 healthy controls. The IL-18 serum levels were measured by IL-18 ELISA kit, to evaluate the activity of Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score. The results showed significant increase in serum IL-18 level in patients with LN (174.09±33.19) than both lupus non nephritis patients (9139.45±64.39) and healthy control (46.06±16.42), with significant correlation between IL-18 level and SLEDAI.
Profit and Preferable Itemsets- A Study

1,2,3 Assistant Professor, Dept Of Cse, Nalla Narasimha Reddy Educational Society's Group Of Institutions, Hyderabad, Ap, India. 4 Assistant Professor,Dept Of Cse, Vaagdevi College Of Engineering,Bollikunta,Warangal,Ap,India. __________________________________________________________________________________________ Abstract:High utility itemset mining is a research area of utility based descriptive data mining, aimed at finding itemset that contributes most to the total utility. A specialized form of high utility itemset mining is utility-frequent itemset mining, which – in addition to subjectively defined utility – also takes into account itemset frequencies. This paper presents a profitable and preferable within the given utility and support constraints threshold. An extensive performance study using both synthetic and real data sets is reported to verify the effectiveness and efficiency of proposed algorithms.
Spatial distribution pattern of European hake, Merluccius merluccius (Pisces: Merlucciidae), in the Mediterranean Sea ; Patrón de distribución espacial de la merluza europea Merluccius merluccius (Pisces: Merlucciidae) en el mar Mediterráneo

Letizia Sion 1, Walter Zupa 2, Crescenza Calculli 3, Germana Garofalo 4, Manuel Hidalgo 5,13, Angélique Jadaud 6, Evgenia Lefkaditou 7, Alessandro Ligas 8, Panagiota Peristeraki 9,10, Isabella Bitetto 2, Francesca Capezzuto 1, Roberto Carlucci 1, Antonio Esteban 11, Cristina Follesa 12, Beatriz Guijarro 13, Zdravko Ikica 14, Igor Isajlovic 15, Giuseppe Lembo 2, Chiara Manfredi 16, José Luis Pérez 13, Cristina Porcu 12, Ioannis Thasitis 17, George Tserpes 18, Pierluigi Carbonara 2
Philosophical bases of research methods : An integrated narrative review

This narrative review examined the philosophical bases of research methods in terms of: (1) ontology; (2) epistemology; (3) axiology; and (3) methodology. It explored the diversities and similarities between paradigms. Three search strategies were observed including: (1) data search for published research; (2) public engine and manual search; and (3) stakeholders input. Subthemes under ontological assumptions are: (1) singular vs. plural reality; (2) empirical vs. subjective reality; (3) scientific vs. sensuous reality; (4) when the singularity and plurality of reality converge; (5) definitive vs. subjective truth; (6) continuum versus polarity; (7) what really is real; (8) truth, reality and knowledge; and (9) seeing the truth and reality of an objective/subjective from a different perspective. Subthemes under axiological assumptions are: (1) fact-value divide/dichotomy; and (2) ethics. Subthemes under methodological assumptions are: (1) scientific versus naturalism: hard versus soft science; (2) convergence and divergence; (3) linearity is only in the books and not in practice; (4) hard or easy; (5) theory, frameworks and literature review; (6) nonstatistical approaches in positivistic approaches; and (7) complementarity. The focus of the lens is guided by philosophical stances. Each paradigm seeks truth, reality and knowledge. Though quantitative inquiry claimed objectivity and qualitative inquiry claim subjectivity, both unconsciously observe the same processes. The division is a continuum that delights its deficiencies. It is when divergence converges.
Student Learning of Perceptual Skills Related to Differentiating Motor Speech Disorders

Purpose: This study aimed to determine if Speech-Language Pathology (SLP) graduate students’ perceptual skills improved after taking an MSD course by comparing pre- and posttest performance. The potential relationship between posttest perceptual-skills performance and academic performance was also investigated.Method: Before beginning instruction in MSD course content, students in a Master’s program in SLP were given a pretest (The Baseline & Post Learning Assessment of Listening & Diagnostics Skills (BPLALDS; Duffy, n.d.a)). Throughout the semester, students were exposed to didactic learning in the classroom supplemented by audio and video modules. At the end of the course, the BPLALDS was used as a posttest. Variation in perceptual skills development was described and compared to overall course performance. Results: Scores on posttests of perceptual ability were significantly higher than pretest scores. Post-hoc comparisons revealed that students who learned relatively more were those who generalized perceptual knowledge to novel stimuli. Academic grade assignment correlated strongly with but accounted for only some of the variation in perceptual ability. Conclusion: Although some variation in perceptual ability related to differentially diagnosing motor speech disorders can be accounted for by academic attainment, additional factors, such as students’ ability to generalize knowledge from novel to new cases, likely contribute. The authors reflect on the manner in which learning theory can inform these results.
Initial bounds for analytic and bi-univalent functions by means of (p,q)−Chebyshev polynomials deﬁned by differential operator

In this paper, a subclass T ζ Σ (m, γ, λ, p, q) of analytic and bi-univalent functions by means of (p, q)−Chebyshev polynomials is introduced. Certain coefficient bounds for functions belong to this subclass are obtained. In addition, the Fekete-Szegö problem is solved in this subclass.
Model of Study Results in Master Degree at Faculty of Management in Jindřichův Hradec

A recent increase of university capacities in the Czech Republic together with present demographical decrease in the cohort of applicants results in a significant change of behavior of students and raises the need to change a strategy of university marketing. In last years, the management of many Czech universities faced a serious issue of significantly lower numbers of applicants and substantially higher rate of unsuccessful finish of studies or prolongation of the study period. At Faculty of Management in Jindřichův Hradec the above mentioned problem appeared to be significant in the Bachelor’s Degree, particularly in the blended learning form. The numbers of students comprises a basis of a significant part of universities funding in the Czech Republic. The goal of this paper is to search for the most important factors influencing study results of Master’s Degree of Faculty of Management. Since the variables describing study data are categorical, for the analysis of important factors we can employ means of probabilistic analysis of dependency structure, particularly so called compositional models. The compositional models rank among the means of probabilistic modeling and present an alternative capable of representing and modeling dependency structures without the necessity to employ graphical apparatus of directed acyclic graphs (unlike the Bayesian networks rather confusingly hinting at non-existing causal relations).
Innovation in the UK music festival; industry: Analysing the role and impact of knowledge management

The UK music festival industry is currently experiencing a period of growth, with an increase in market value from £1.5 billion in 2013 to an estimated value of £2.2 billion in 2017 (Mintel Group Ltd, 2017). Alongside the rising number of events and attendees the industry competition that music festivals face is also increasing (Anderton, 2009). To compete in an increasingly competitive sector, festivals are required to find ways of differentiating themselves from their competition (Getz, 2002; Faulkner, 2003), to generate competitive advantage.
Bank Competition, Cost of Credit and Economic Activity: evidence from Brazil

We estimate the effect of bank competition on financial and real variables. To do so, we use regional heterogeneous exposure to mergers and acquisitions (M&A) of large banks as an instrument for changes in competition of local banking markets in Brazil. We use detailed administrative data on loans and firms and a difference-in-differences empirical strategy that compares changes in outcomes for markets affected or not by the M&A episodes. We find that, following M&A episodes, spreads increase and lending decreases persistently in exposed markets relative to controls. We show that this is larger for more concentrated markets at the time of the M&A episode, and is unlikely to be driven by other factors, such as branch closures. We find that non-agricultural employment falls . 2% for an increase of 1% in spreads. We develop a model of heterogeneous firms and concentration in the banking sector that is consistent with the micro evidence. In our model, the semi-elasticity of credit to lending rates is a sufficient statistic for the effect of concentration on output, which we estimate to be -3.17. Among other counterfactuals, we show that if Brazilian spreads fell to world levels, output would increase by approximately 5%.
Upper and Lower Bounds on the Space Complexity of Detectable Objects

The emergence of systems with non-volatile main memory (NVM) increases the interest in the design of recoverable concurrent objects that are robust to crash-failures, since their operations are able to recover from such failures by using state retained in NVM. Of particular interest are recoverable algorithms that, in addition to ensuring object consistency, also provide detectability, a correctness condition requiring that the recovery code can infer if the failed operation was linearized or not and, in the former case, obtain its response. In this work, we investigate the space complexity of detectable algorithms and the external support they require. We make the following three contributions. First, we present the first wait-free bounded-space detectable read/write and CAS object implementations. Second, we prove that the bit complexity of every N-process obstruction-free detectable CAS implementation, assuming values from a domain of size at least N, is Ω (N). Finally, we prove that the following holds for obstruction-free detectable implementations of a large class of objects: their recoverable operations must be provided with auxiliary state - state that is not required by the non-recoverable counterpart implementation - whose value must be provided from outside the operation, either by the system or by the caller of the operation. In contrast, this external support is, in general, not required if the recoverable algorithm is not detectable.