Miracle-dz/UniFAR-FTUs huggingface dataset:
An assessment of candidate genes to assist prognosis in gastric cancer.

Background Gastric cancer (GC) is the fourth commonest cancer worldwide, with the second highest mortality rate. Its poor mortality is linked to delayed presentation. There is a drive towards non-invasive biomarker screening and monitoring of many different types of cancer, although with limited success so far. We aimed to determine if any genes from a 32-gene panel could be used to determine GC prognosis. Methods We carried out a retrospective study on the expression of 32 genes, selected for their proven or potential links to GC, on historic formalin fixed paraffin-embedded (FFPE) GC specimens from our unit. Gene expression was measured using quantitative nuclease protection assays (qNPA) technology. Following statistical analysis of the results, immunohistochemical staining for eight genes, both discriminating and non-discriminating, was conducted in seven age and sex matched non-metastatic: metastatic GC pairings. The stained samples were reviewed by two blinded consultant histopathologists. Results Multivariate Cox analysis of the gene expression data revealed metastatic status, age, sex and five genes appeared to influence GC survival. Genes negatively influencing survival included BCAS1, P53 and HSP90AA1 (relative risks 2.20, 3.73 and 7.53 respectively). Genes conveying survival benefit included CASP3 and TERT (relative risks 0.10 and 0.24 respectively). Immunohistochemical staining of seven age and sex matched non-metastatic: metastatic pairs revealed no association between gene expression and protein expression. Conclusions Our study found several genes whose expression may affect GC prognosis. However, immunohistochemical analysis revealed no association between gene expression and protein expression. It remains to be determined whether gene expression or protein expression are reliable means of assessing GC prognosis.
Studies on the developmental stages of hammerheadShark Sphyrna (eusphyrna) blochil fromThe Gulf of Mannar

Various stages of intra-uterine embryos of Sphyrna blocliii collected from the Gulf of Mannar are described and discussed. Uterine compartments are formed in this species which exhibit multipb pregnancy. An embryonic membrane store ch.amiber is present in each uterine comrpartment. The placenta of this species is of yolk-sac type and is formed at the stage in between 125 mm and 210 mm; yolk persist in the yolk-sac even when the placental connection is established with the mother. The placantation process observed in this species is almost similiar to that of S. tiburo and Carcltarhinus dussumieri. The probable gestation period and other details of placentation are discussed.
Clinical Healing Process and Symptoms of Two Cases of Chronic Periapical Lesions Treated with Er , Cr : YSGG Laser

on good shaping, cleaning, disinfection, and filling of the canals.6,7 Just like in every dental treatment, there is always a risk of failure in root canal treatments. As reported before, with ideal conditions for root canal therapy, the success rate is 90%, but for teeth with periapical radiolucency, it is only about 80%. 5 In order to raise these rates, the treatment periods should be decreased, root canal systems should be free of smear layer, and techniques and materials for disinfection and filling should be improved.2,5-7 Research on lasers in dentistry started in the 1960s.2,4 Laser therapy for root canal treatment represented a new approach to more successful treatments. Various lasers can be used for disinfecting the canals. The Er,Cr:YSGG hydrokinetic system laser (YSGG) (Erbium, Chromium, Yttrium, Scandium, Gallium, Garnet) (Fig 1) with a wavelength of 2780 nm, frequency of 20 Clinical Healing Process and Symptoms of Two Cases of Chronic Periapical Lesions Treated with Er,Cr:YSGG Laser
Financial Sector Reform after the Subprime Crisis: Has Anything Happened?

We analyze the reactions of stock returns and the spreads of credit default swaps (CDS) of banks from Europe and the USA to four major regulatory reforms in the aftermath of the subprime crisis, employing an event study analysis. Contrary to public perception, we find that financial markets indeed reacted to the structural reforms enacted at the national level. The reforms succeeded in reducing bail-out expectations relative to the post-bail-out period, especially for systemic banks. The strongest effects were found for the Dodd–Frank Act and in particular for the Volcker rule. Bank profitability was affected in all countries, showing up in lower equity returns.
Islamic Social Business to Alleviate Poverty and Social Inequality

Purpose – The purpose of this paper is to identify some well-set instruments in Islam that can efficiently alleviate poverty, solve social problems and reduce social inequality through a new operational framework called “Islamic social business (ISB)”. Design/methodology/approach – This is a conceptual research that is based on Al-Quranic principles as well as contemporary social welfare philosophies, such as, augmented stakeholder theory, social enterprise and social business. Al-Quran, Al-Hadith and existing traditional and Islamic literature are consulted for this study. Findings – The study proposes an efficient system of Islamic wealth sourcing and management to make the process of poverty alleviation sustainable. Other social problems for disadvantaged people, such as, health-, shelter-, literacy- and environmental-related issues are also addressed in the proposed system. The study identifies the inefficiency in the current practices and makes some propositions that are in conformance with Islamic p.
AEG-1 Contributes to Metastasis in Hypoxia-Related Ovarian Cancer by Modulating the HIF-1alpha/NF-kappaB/VEGF Pathway

Objective Ovarian carcinoma represents one of the deadliest malignancies among female cancer patients. Astrocyte-elevated gene-1 (AEG-1) participates in the ontogenesis of multiple human malignant diseases. Here we evaluated AEG-1, hypoxia-inducible factor- (HIF-) 1α, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and vascular endothelial growth factor (VEGF) amounts in hypoxia induced ovarian carcinoma cells. This study aimed to explore the mechanism by which AEG-1 regulates metastasis in hypoxia induced ovarian carcinoma. Patients and Methods AEG-1, HIF-1α, and VEGF protein amounts were evaluated by immunohistochemistry in 40 and 170 normal ovary and ovarian cancer tissue specimens, respectively. In addition, AEG-1, HIF-1α, NF-κB, and VEGF mRNA and protein levels were determined by reverse quantified RT-PCR and WB, respectively, at different time periods (0–24 h) in epithelial ovarian cancer (EOC) SKOV3 cells treated in a hypoxia incubator. Furthermore, NF-κB and VEGF gene and protein expression levels in AEG-1 knockdown EOC cells were quantitated by RT-PCR and WB, respectively. Results AEG-1, HIF-1α, and VEGF amounts were significantly elevated in EOC tissue samples compared with normal ovary specimens (p < 0.001). Positive expression of HIF-1α and AEG-1 was associated with higher metastatic rate (p < 0.01), lower FIGO stage (p < 0.001), and degree of differentiation (p < 0.001). Meanwhile, EOC SKOV3 cells grew upon exposure to hypoxia for 8 h (p < 0.001); at this time point, AEG-1, HIF-1α, NF-κB, and VEGF amounts peaked (p < 0.001), at both the gene and the protein levels. After AEG-1 knockdown, HIF-1α, NF-κB, and VEGF amounts were significantly decreased in EOC SKOV3 cells, also under hypoxic conditions (p < 0.01). Conclusions As an independent prognostic factor, AEG-1 was found to be significantly associated with hypoxia in ovarian cancer by regulating the HIF-1alpha/NF-kappaB/VEGF pathway. Therefore, AEG-1 may be useful in determining disease stage and prognosis in ovarian cancer.
Portfolio Performance Measurement: Monotonicity with Respect to the Sharpe Ratio and Multivariate Tests of Correlation

This paper shows that there is a broad class of probability distributions for fund returns under which many well-known performance measures are monotonically increasing functions of the Sharpe ratio. It also reports results showing conditions under which monotonicity can fail. The paper shows that under regularity conditions the asymptotic correlation between pairs of performance measures is equal to unity. This result is used to derive unconditional and conditional multivariate tests of unit correlation between an arbitrary number of performance measures. A study of UK investment trusts supports the results.
Predictors of surgical intervention for hepatocellular carcinoma: race, socioeconomic status, and hospital type.

OBJECTIVES To define current use of surgical therapies for hepatocellular carcinoma (HCC) and evaluate the correlation of various patient and hospital characteristics with the receipt of these interventions. DESIGN Retrospective cohort. SETTING California Cancer Registry data linked to the Office of Statewide Health Planning and Development patient discharge abstracts between 1996 and 2006. PATIENTS Patients with primary HCC. MAIN OUTCOME MEASURES Receipt of liver transplant, hepatic resection, or local ablation. RESULTS Of 12,148 HCC cases, 2390 (20%) underwent surgical intervention. Three hundred eleven (2.56%) received a liver transplant, 1307 (10.8%) underwent resection, and 772 (6.35%) had local ablation. There were wide variations in treatment by race and hospital type. African American and Hispanic patients were less likely than white patients to undergo transplant (P < .05). African American and Hispanic patients were less likely than white and Asian/Pacific Islander patients to have hepatectomy or ablation (P < .05). In multivariable analysis, the apparent differences in surgical intervention by race/ethnicity were decreased when adjusting for the patients' socioeconomic and insurance statuses. Patients with lower socioeconomic status and no private insurance were less likely to receive any surgery (P < .01). Hospital characteristics also explained some variations. Disproportionate Share Hospitals and public, rural, and nonteaching hospitals were less likely to offer surgical treatment (P < .01). CONCLUSION There are significant racial, socioeconomic, and hospital-type disparities in surgical treatment of HCC.
Autotelic Principle: the role of intrinsic motivation in the emergence and development of artificial language. (Autotelic Principle : le rôle de la motivation dans l'apparition et le développement d'un langage artificiel)

This thesis studies the role of intrinsic motivation in the emergence and development of communicative systems in populations of artificial agents. To be more specific, our goal is to explore how populations of agents can use a particular motivation system called autotelic principle to regulate their language development and the resulting dynamics at the population level.To achieve this, we first propose a concrete implementation of the autotelic principle. The core of this system is based on the balance between challenges, tasks to be done to achieve a goal, and skills, the abilities the system can employ to accomplish the different tasks. The relation between the two elements is not steady but regularly becomes destabilised when new skills are learned, which allows the system to attempt challenges of increasing complexity. Then, we test the usefulness of the autotelic principle in a series of language evolution experiments. In the first set of experiments, a population of artificial agents should develop a language to refer to objects with discrete values. These experiments focus on how unambiguous communicative systems can emerge when the autotelic principle is employed to scaffold language development into stages of increasing difficulty. In the second set of experiments, agents should agree on a language to communicate with about colour samples. In this part, we explore how the motivation system can regulate the linguistic complexity of interactions for a continuous domain and examine the value of the autotelic principle as a mechanism to control several language strategies simultaneously. To summarise, we have shown through our work that the autotelic principle can be used as a general mechanism to regulate complexity in language emergence in an autonomous way for discrete and continuous domains.
Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis

Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expression profiles GSE25097, GSE45267, GSE57957 and GSE62232 were downloaded from the Gene Expression Omnibus database, including 436 HCC and 94 normal liver tissues. A total of 185 differentially expressed genes (DEGs) were identified in HCC, including 92 upregulated genes and 92 downregulated genes. Gene ontology (GO) was performed, which revealed that the upregulated DEGs were primarily enriched in cell division, mitotic nuclear division, mitotic cytokinesis and G1/S transition of the mitotic cell cycle. Pathway enrichment was analyzed based on the Kyoto Encyclopedia of Genes and Genomes database to assess the functional relevance of DEGs. The most significant module was selected from protein-protein interactions and 15 important hub genes were identified. The sub-networks of hub genes were involved in cell division, p53 signaling, and T lymphotropic virus type I infection signaling pathways. In conclusion, the present study revealed that the identified DEG candidate genes may promote the understanding of the cause and molecular mechanisms underlying the development of HCC and that these candidates and signal pathways may be potential targets of clinical therapy for HCC.
Part-of-Speech Tagging for Arabic Gulf Dialect Using Bi-LSTM

Part-of-speech (POS) tagging is one of the most important addressed areas in the natural language processing (NLP). There are effective POS taggers for many languages including Arabic. However, POS research for Arabic focused mainly on Modern Standard Arabic (MSA), while less attention was directed towards Dialect Arabic (DA). MSA is the formal variant which is mainly found in news and formal text books, while DA is the informal spoken Arabic that varies among different regions in the Arab world. DA is heavily used online due to the large spread of social media, which increased research directions towards building NLP tools for DA. Most research on DA focuses on Egyptian and Levantine, while much less attention is given to the Gulf dialect. In this paper, we present a more effective POS tagger for the Arabic Gulf dialect than currently available Arabic POS taggers. Our work includes preparing a POS tagging dataset, engineering multiple sets of features, and applying two machine learning methods, namely Support Vector Machine (SVM) classiﬁer and bi-directional Long Short Term Memory (Bi-LSTM) for sequence modeling. We have improved POS tagging for Gulf dialect from 75% accuracy using a state-of-the-art MSA POS tagger to over 91% accuracy using a Bi-LSTM labeler.
Supporting Private Data on Hyperledger Fabric with Secure Multiparty Computation

Hyperledger Fabric is a "permissioned" blockchain architecture, providing a consistent distributed ledger, shared by a set of "peers. " As with every blockchain architecture, the core principle of Hyperledger Fabric is that all the peers must have the same view of the shared ledger, making it challenging to support private data for the different peers. Extending Hyperledger Fabric to support private data (that can influence transactions) would open the door to many exciting new applications, in areas from healthcare to commerce, insurance, finance, and more. In this work we explored adding private-data support to Hyperledger Fabric using secure multiparty computation (MPC). Specifically, in our solution the peers store on the chain encryption of their private data, and use secure MPC whenever such private data is needed in a transaction. This solution is very general, allowing in principle to base transactions on any combination of public and private data. We created a demo of our solution over Hyperledger Fabric v1.0, implementing a bidding system where sellers can list assets on the ledger with a secret reserve price, and bidders publish their bids on the ledger but keep secret the bidding price itself. We implemented a smart contract (aka "chaincode") that runs the auction on this secret data, using a simple secure-MPC protocol that was built using the EMP-toolkit library. The chaincode itself was written in Go, and we used the SWIG library to make it possible to call our protocol implementation in C++. We identified two basic services that should be added to Hyperledger Fabric to support our solution, and are now working on implementing them.
Intergenerational inequalities in standards of living in France

[eng] In this article, the effects of age (or lifecycle) and generation on the standard of living are estimated using a pseudo-panel developed from the various editions of the French Household Expenditure Survey (Budget de famille - BdF) between 1979 and 2011. The standard of living of households is calculated using the disposable income or the private consumption per consumption unit, including and excluding expenditure on housing and imputed rent. Using the identification strategy developed by Deaton and Paxson (1994) for Age-Period-Cohort (APC) models produces two main results. Firstly, the standard of living increases significantly with age from 25 to 64 years old. For example, consumption is 35% greater for 50-54 year olds than for 25-29 year olds. From 65 years old, changes depend on the living standard indicator considered. Furthermore, the standard of living of the baby boom generations is higher than generations born before the Second World War, but lower than or equal to the generations that follow. For example, the consumption of the cohort born in 1946 is 40% higher than the cohort born in 1926, but 20% lower than the cohort born in 1976. Considering all cohorts born between 1901 and 1979, no generation has been less fortunate than its ancestors. Discussion of these results demonstrates their robustness, particularly with regard to the results of other identification strategies, including the Age-Period-Cohort-Detrended (APCD) method which removes the linear trend from variables, and an original strategy, the Life Expectancy-Period-Cohort method (LEPC) which replaces the age variable with the life expectancy at each age. It shows the significance of economic growth in increasing the standard of living of generations and confirms that no generation has consumed less than the generations preceding it.
Value Portfolio Theory

This paper considers the role of valuation in portfolio theory. In particular, we examine value-price ratios and their dynamic properties. Five valuation principles are proposed, namely the separability of prices and valuations, the asymptotic convergence of value-price ratios, the finite horizon convergence of value-price ratios, the predictability of asset returns using value-price ratios, and the irrelevance of terminal values for return predictability. We then consider the use of value-price ratios in optimising portfolio weights. First, we estimate three systems of value-price return predictability using GMM. The first system is based on own-asset predictability, the second uses cross-asset return predictability, and the third uses a mean-reverting specification. The coefficients of return predictability and the covariance matrix of the residuals from the return predictability regressions are used to construct portfolio weights and form the value portfolios. For a sample of 60 US stocks from December 1979 to November 1998, the value portfolios are compared to standard Markowitz portfolios. The comparisons are invoked for portfolios formed across sectors, industries and sub-industries. The results show that value portfolios exhibit superior performance for portfolios where the assets are relatively homogeneous. The more refined the classification, the better the performance. Thus, value portfolios perform better for sub-industries than for industries, and better for industries than for sectors. In general, value-price predictability confers benefits for portfolio performance when portfolios are small and homogeneous.
The impact of azole antifungal drugs on imatinib metabolism in human liver microsomes

Abstract 1. Imatinib is widely used for the treatment of hematologic malignancies. It is common that imatinib is clinically co-prescribed with azole antifungal agents since these patients are more prone to invasive antifungal infection. The present study was to investigate the effects of azole antifungal drugs, including ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole on imatinib metabolism. 2. The main metabolites, 1-OH midazolam and N-desmethyl imatinib, were determined in the absence and in the presence of various levels of ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole. The relevant assay was also performed to screen mechanism-based inhibitors (MBI). 3. The inhibition ability of 1-OH midazolam formation from midazolam based on IC50 values was ketoconazole (0.09 µM)>itraconazole (0.31 µM)> posaconazole (0.68 µM)>voriconazole (2.10 µM) > fluconazole (8.90 µM). Similarly, the rank order of inhibitory effects on formation of N-desmethyl imatinib from imatinib was ketoconazole (4.58 µM)>itraconazole (17.45 µM)> posaconazole (31.02 µM)> voriconazole (367.9 µM) >fluconazole (1.11 mM). Posaconazole and itraconazole displayed evidence of MBI. Additionally, imatinib was also shown as a MBI of CYP3A with IC50 value of 5.40 µM against the midazolam. 4. The significant difference in IC50 values of midazolam and imatinib inhibited by azole antifungal agents was observed. The role of CYP2C8 in imatinib metabolism and imatinib autoinhibits CYP3A activity may explain this difference. Our findings suggest that the azole antifungal agents might have limited impacts on imatinib exposure by CYP3A activity.
Active Learning of GAV Schema Mappings

Schema mappings are syntactic specifications of the relationship between two database schemas, typically called the source schema and the target schema. They have been used extensively in formalizing and analyzing data inter-operability tasks, especially data exchange and data integration. There is a growing body of research on deriving schema mappings from data examples, that is, pairs of source and target instances that depict the behavior of the unknown schema mapping. One of the approaches used in this endeavor casts the derivation of a schema mapping from data examples as a learning problem. Earlier work has shown that GAV mappings (global-as-view schema mappings) are learnable in Angluin's model of exact learning with membership queries and equivalence queries. Here, we validate the practical applicability of this theoretical result by designing and implementing an active learning algorithm, called GAV-Learn that derives a syntactic specification of a GAV mapping from a given set of data examples and from a "black-box" implementation. We analyze the properties of GAV-Learn and, among other results, we show that it produces a GAV mapping that has minimal size and is a good approximation of the unknown GAV mapping. Furthermore, we carry out a detailed experimental evaluation that demonstrates the effectiveness of GAV-Learn along different metrics. In particular, we compare GAV-Learn with two earlier approaches for deriving GAV mappings from data examples, and establish that it performs significantly better than the two baselines.