Miracle-dz/UniFAR-FTUs huggingface dataset:
Hedgehog Signalling and Tumour-initiating cells as Radioresistance Factors in Esophageal Adenocarcinoma

Clinical management of esophageal adenocarcinoma (EAC) relies on radiation therapy, yet radioresistance is a pervasive challenge in this disease. The mechanisms of EAC radioresistance remain largely unknown due to a paucity of validated preclinical models. The present studies report on the development of seven primary xenograft models established from patient tumours. These models are used to interrogate the range of radiosensitivities and mechanisms of radioresistance in EAC tumours. We found that radiation enriches the tumour-initiating cell population in two xenograft lines tested. Furthermore, three tested xenograft lines respond to irradiation by upregulating Hedgehog transcripts, a pathway involved in stem cell maintenance and proliferation. Upregulation occurs in autocrine and paracrine patterns simultaneously, suggesting that Hedgehog signalling may have a complex role in the radioresponse of EAC tumours. These findings suggest that inhibiting stem cell pathways in combination with radiotherapy may have an important role in the clinical management of EAC.
Stock Price Prediction using Machine Learning and Swarm Intelligence

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this paper, a novel machine learning approach, which works in two phases, is introduced to predict the price of a stock in the next day based on the information extracted from the past 26 days. In the first phase of the method, an automatic clustering algorithm clusters the data points into different clusters, and in the second phase a hybrid regression model, which is a combination of particle swarm optimization and support vector regression, is trained for each cluster. In this hybrid method, particle swarm optimization algorithm is used for parameter tuning and feature selection. Results: The accuracy of the proposed method has been measured by 5 companies’ datasets, which are active in the Tehran Stock Exchange market, through 5 different metrics. On average, the proposed method has shown 82.6% accuracy in predicting stock price in 1-day ahead. Conclusion: The achieved results demonstrate the capability of the method in detecting the sudden jumps in the price of a stock.
PERFORMANCE ELEITORAL DOS PARLAMENTARES E ALOCAÇÃO DE RECURSOS NOS MUNICÍPIOS: EFEITO DOS DISTRITOS INFORMAIS

Esta pesquisa busca investigar qual o efeito produzido pela votacao dos deputados federais eleitos nos estados da Paraiba e Pernambuco, e seu comportamento relativo a apresentacao e execucao de emendas. Os dados foram coletados nos bancos do Tribunal Superior Eleitoral - TSE (eleicoes gerais do Brasil de 2014) e a respectiva legislatura, utilizando dados das emendas apresentadas pelos referidos parlamentares nos anos de 2016, 2017 e 2018, dados disponiveis no banco SigaBrasil do Senado Federal. Por meio de estatistica descritiva, o estudo possibilitou expor um panorama do perfil dos deputados e suas atuacoes em relacao a apresentacao de emendas. Tais analises consideram que a distincao entre emendas direcionadas a municipios e aos estados, em sua totalidade, pode estar associada ao padrao de distribuicao de votos obtidos pelos deputados.
Institutional fragmentation and urbanization in European Union cities

ABSTRACT The relationship between institutional fragmentation and the spatial extent of cities in Europe’s functional urban areas is examined. European Union planning regulations vary across member states, but in most cases local authorities determine land use within the more general regulatory frameworks set by national or subnational authorities. More decentralized and fragmented settings may favour urban sprawl, allowing developers to avoid land-use restrictions in one municipality by moving to adjacent ones and providing incentives for municipalities to adopt less strict land-conversion regulations to attract households and workers. The empirical results fully support this hypothesis and unveil significant differences between small and large cities, the effect of governance fragmentation being a substantial factor in the latter case.
Phytoplankton species richness, evenness, and production in relation to nutrient availability and imbalance

We used natural phytoplankton communities from four coastal regions to test diversity‐functioning relationships, relations of N2‐fixing cyanobacteria to nutrient imbalance, and the importance of metacommunity dynamics. Resource availability was measured as total nitrogen and phosphorus. Resource imbalance was determined as (1) the ratio of dissolved inorganic nitrogen to total phosphorus and (2) an experimentally verified indicator quantified by modelling responses in 14C‐based primary production to nutrient additions. Resource availability explained variance in biomass, productivity, and species richness, as expected by the Species Energy Theory, but not evenness. Linear mixed‐effects models confirmed the overall relation between productivity and resource availability, whereas other resource availability relations showed also notable clustering by region. The Resource Ratio Theory predicting that diversity increases with the number of limiting resources was not supported. Nutrient imbalance had a weak effect on the biomass of N2‐fixing cyanobacteria, but not their share of total phytoplankton biomass. Contrary to many previous studies on biodiversity‐ecosystem functioning relationships, we found a highly significant inverse relationship between evenness and biomass. This indicates that species‐rich natural phytoplankton communities form the basis for opportunistic species to temporarily monopolize resources and create blooms. The result was consistent across regions, although their community composition differed. Metacommunity dynamics were important, since distance between the regions explained higher percentage of the variability than local resources together. As the species able to monopolize resources vary widely in their role for aquatic food webs and environmental consequences (e.g., food quality, toxicity), species‐level trait data is essential to understand better diversity‐productivity relationships.
Impact of Off Periods on Persons With Parkinson Disease and Care Partners

Background The definition of off periods proposed in 2018 emphasizes functional disability as part of the off period experience, but limited research to date investigates the functional impact of off periods on persons with Parkinson disease and care partners. This study aimed to investigate the impact of off periods on both persons with Parkinson disease and care partners through interviews of dyads living with motor and/or nonmotor fluctuations. Methods Investigators performed interviews separately with persons with Parkinson disease and care partners using a semistructured questionnaire. Investigators used a qualitative descriptive approach to identify themes in interview transcripts relating to the impact of off periods on daily life. Identified themes were subsequently organized using World Health Organization quality of life domains. Results Twenty persons with Parkinson disease and their care partners (total n = 40) participated in interviews. Persons with Parkinson disease described impairments in level of independence (e.g., relating to employment, mobility, activities of daily living, and medication timing), socialization, leisure activities, driving, physical function, and psychological experiences relating to off periods. Care partners reported off period impacts on their own independence, socialization, leisure, and psychological experiences. Conclusions Clinicians should query the daily impact of off periods on both persons with Parkinson disease and care partners at clinical visits to inform treatment decisions and counseling. Measures of off period impact should be incorporated into clinical trials targeting fluctuations to fully understand the effects of interventions for fluctuations.
The extent of genotype-specific humoral immunity produced on infection with hepatitis C virus: relevance for serological screening and diagnosis

Blood transfusion services around the world screen donations for antibodies to hepatitis C virus (HCV). One potential problem of this is that the antibody response only becomes detectable several weeks after infection and potentially infectious donations in the "window period" go undetected. The screening ELISA tests are based upon genotype 1 sequence. Six distinct HCV genotypes exist, which show approximately 30 % amino acid sequence divergence in their encoded proteins. Sequence variability is not uniform across the genome, being greatest in the regions encoding envelope proteins and most restricted in the core gene. Sequence variation in the antigenic determinants in core, NS3, NS4A/B and NS5A/B proteins, may produce genotype-specific antibodies which do not crossreact with the antigens used in current screening assays for detection ofantibody to HCV. Reduction in test sensitivity caused by genotype-specific reactivity may particularly affect detection of antibody around the time of seroconversion, as antibody reactivity is likely to be weak and restricted to a limited number of epitopes. The extent of type-specific and type-common components of the humoral immune response were investigated by measuring the antibody levels in samples of each genotype with type-homologous and type-heterologous antigens. Reactivity directed against the individual genotype 1 antigens used in a commercially available anti-HCV screening assay (VK48; Murex Biotech) was compared with corresponding core, NS3 and NS4A/B antigens of genotype 3, and NS3, NS4A/B and NS5A/B antigens from genotype 4 using a panel of samples from individuals infected with different genotypes (genotype 1: n=33, 3: n=34 and 4: n=43). A combined ELISA was subsequently assembled using the core, NS3 and NS5A/B recombinant proteins and NS4A/B synthetic peptide of genotype 3 a sequence, and serological reactivity in this ELISA compared quantitatively with reactivity in the (type 1-based) Murex VK48 assay, using a similar panel of samples from individuals infected with different HCV genotypes. The overall proportion of typespecific reactivity in the combined ELISAs was 46% (with the type-common component making up the other 54%). Type-specificity ofreactivity to each region depended on the extent of amino acid divergence between genotypes, with the more conserved core region eliciting 26% type-specific reactivity, compared with 60% and 62-77% to the NS3 and NS5A/B regions.
Natalizumab in patients with multiple sclerosis in Colombia: a case series

resultados: Dieciocho pacientes (82)% alcanzaron el estado NEDA en un tiempo medio de seis meses. Siete pacientes (32%) dieron positivo para anticuerpos anti-virus JC. Sin embargo, ninguno desarrolló leucoencefalopatía multifocal progresiva. Durante el periodo de seguimiento cinco pacientes (23%) presentaron nuevas lesiones y 17 pacientes (77%) tuvieron recaídas antes de alcanzar el estado NEDA.
Is competition an interaction as relevant as predation for tropical planktonic cladocerans

Abstract: Aim: The relevance of competition and predation for the two most abundant and frequent cladoceran populations, the medium-sized Ceriodaphnia richardi Sars 1901 and the large-sized Daphnia gessneri Herbst 1967, in a tropical shallow lake. Methods: Laboratory experiments and weekly samplings in the lake for a year were used to evaluate: density fluctuations and reproduction; predation on juveniles and adults by larvae of Chaoborus brasiliensis Theobald 1901; competitive interactions and possible implications of competition and predation on the fluctuations in the lake. Juveniles and adults of both cladocerans were offered to instar IV of chaoborid, for testing selective predation in laboratory experiment. Competitive interaction between the two cladocerans was tested in experiments, with high (0.70 mg C.L -1 ) and low (0.25 mg C.L -1 ) concentrations of the edible chlorophycean Desmodesmus spinosus Chodat. Results: C. richardi and D. gessneri were more abundant in the cool season, when their densities were inversely correlated, and when invertebrate predators, C. brasiliensis and the water mite Krendowskia sp. , were less abundant. Despite higher concentrations of food and larger number of offsprings produced by the cladocerans in the warm season in the lake, their densities were lower, coincident with the increase of invertebrate predators, mainly chaoborid. C. brasiliensis preyed on adult C. richardi and on young D. gessneri . In the competition experiments, the densities and the population growth rates of C. richardi were higher than those of D. gessneri . The competition results support the “small body size” and the “ r- max” hypotheses. The exclusion of D. gessneri by C. richardi occurred only in experimental conditions, while they coexist in the lake, but without reaching their carrying capacity. Conclusions: Predation is the key factor influencing the populations of cladocerans, whereas competition seems to play a secondary role, probably restricted to some periods of lower food concentration in the cool season.
Advanced Prediction of Roadway Broken Rock Zone Based on a Novel Hybrid Soft Computing Model Using Gaussian Process and Particle Swarm Optimization

A simple and accurate evaluation method of broken rock zone thickness (BRZT), which is usually used to describe the broken rock zone (BRZ), is meaningful, due to its ability to provide a reference for the roadway stability evaluation and support design. To create a relationship between various geological variables and the broken rock zone thickness (BRZT), the multiple linear regression (MLR), artificial neural network (ANN), Gaussian process (GP) and particle swarm optimization algorithm (PSO)-GP method were utilized, and the corresponding intelligence models were developed based on the database collected from various mines in China. Four variables including embedding depth (ED), drift span (DS), surrounding rock mass strength (RMS) and joint index (JI) were selected to train the intelligence model, while broken rock zone thickness (BRZT) is chosen as the output variable, and the k-fold cross-validation method was applied in the training process. After training, three validation metrics including variance account for (VAF), determination coefficient (R2) and root mean squared error (RMSE) were applied to describe the predictive performance of these developed models. After comparing performance based on a ranking method, the obtained results show that the PSO-GP model provides the best predictive performance in estimating broken rock zone thickness (BRZT). In addition, the sensitive effect of collected variables on broken rock zone thickness (BRZT) can be listed as JI, ED, DS and RMS, and JI was found to be the most sensitive factor.
Chlorella vulgaris DPSF 01: A unique tool for removal of toxic chemicals from tannery wastewater

The present study investigated the removal of toxic pollutants and reduction of heavy metals from tannery wastewater using Chlorella vulgaris. The physiochemical parameters like pH, electrical conductivity (EC), biological oxygen demand (BOD), chemical oxygen demand (COD), total solids (TS), total dissolved solids (TDS), chloride, total hardness (TH), bicarbonate, magnesium, ammoniacal nitrogen, phosphate and heavy metals (Cu, Cr, Zn, Ni and Fe) were analysed using standard methods. Functional group of toxic chemicals in tannery wastewater and C. vulgaris treated wastewater were analysed by Fourier transforms infrared spectroscopy (FT-IR) and gas chromatography – mass spectrometry (GC-MS). 20 to 60% of chemicals (bicarbonate, chloride, nitrogen, phosphate and magnesium) were reduced by the treatment using C. vulgaris within 28 days. FT-IR and GC-MS analysis reveals that the functional group of azo compounds was not in C. vulgaris treated wastewater. Thus, the results obtained conclude that C. vulgaris can be used as a suitable tool for the removal of toxic chemicals of tannery wastewater. Key words: Chlorella vulgaris, toxic chemicals, tannery wastewater, physio-chemicals, Fourier Transforms Infrared Spectroscopy (FT-IR), Gas Chromatography – Mass Spectrometry (GC-MS).
Structural Mechanisms of the Sliding Clamp and Sliding Clamp Loader: Insights into Disease and Function: A Dissertation

Chromosomal replication is an essential process in all life. This dissertation highlights regulatory roles for two critical protein complexes at the heart of the replication fork: 1) the sliding clamp, the major polymerase processivity factor, and 2) the sliding clamp loader, a spiral-shaped AAA+ ATPase, which loads the clamp onto DNA. The clamp is a promiscuous binding protein that interacts with at least 100 binding partners to orchestrate many processes on DNA, but spatiotemporal regulation of these binding interactions is unknown. Remarkably, a recent disease-causing mutant of the sliding clamp showed specific defects in DNA repair pathways. We aimed to use this mutant as a tool to understand the binding specificity of clamp interactions, and investigate the disease further. We solved three structures of the mutant, and biochemically showed perturbation of partnerbinding for some, but not all, ligands. Using a fission yeast model, we showed that mutant cells are sensitive to select DNA damaging agents. These data revealed significant flexibility within the binding site, which likely regulates partner binding. Before the clamp can act on DNA, the sliding clamp loader places the clamp onto DNA at primer/template (p/t) junctions. The clamp loader reaction couples p/t binding and subsequent ATP hydrolysis to clamp closure. Here we show that composition (RNA vs. DNA) of the primer strand affects clamp loader
A solution of the time paradox of physics

Abstract Quantum mechanics for describing the behavior of microscopic entities and thermodynamics for describing macroscopic systems exhibit separate time concepts. Whereas many theories of modern physics interpret processes as reversible, in thermodynamics, an expression for irreversibility and the so-called time arrow has been developed: the increase of entropy. The divergence between complete reversibility on the one hand and irreversibility on the other is called the paradox of time. Since more than hundred years many efforts have been devoted to unify the time concepts. So far, the efforts were not successful. In this paper a solution is proposed on the basis of matter-energy equivalence with an energetic distinction between matter and mass. By refraining from interpretations predominant in modern theoretical physics, the first and second laws of thermodynamics can be extended to fundamental laws of nature, which are also valid at quantum level.
Towards optimizing the execution of spark scientific workflows using machine learning‐based parameter tuning

In the last few years, Apache Spark has become a de facto the standard framework for big data systems on both industry and academy projects. Spark is used to execute compute‐ and data‐intensive workflows in distinct areas like biology and astronomy. Although Spark is an easy‐to‐install framework, it has more than one hundred parameters to be set, besides domain‐specific parameters of each workflow. In this way, to execute Spark‐based workflows efficiently, the user has to fine‐tune a myriad of Spark and workflow parameters (eg, partitioning strategy, the average size of a DNA sequence, etc.). This configuration task cannot be manually performed in a trial‐and‐error manner since it is tedious and error‐prone. This article proposes an approach that focuses on generating interpretable predictive machine learning models (ie, decision trees), and then extract useful rules (ie, patterns) from these models that can be applied to configure parameters of future executions of the workflow and Spark for nonexperts users. In the experiments presented in this article, the proposed parameter configuration approach led to better performance in processing Spark workflows. Finally, the approach introduced here reduced the number of parameters to be configured by identifying the most relevant domain‐specific ones related to the workflow performance in the predictive model.
The Lethal Interaction Following Plasmodial Fusion between Two Strains of the Myxomycete Physarum polycephalum

Summary: A lethal reaction followed fusion between plasmodia of two strains (15 and 29) of the Myxomycete Physarum polycephalum on a solid medium. Dead areas were seen about 5 h after fusion and increased in size rapidly. Strain 29 was often wholly destroyed but strain 15 commonly survived and subsequently reinvaded the dead areas. Large plasmodia of 29 were destroyed by fusion with small plasmodia of 15, but large plasmodia of 15 survived fusion with small plasmodia of 29. The lethal reaction did not normally occur under conditions of suboptimal nutrition, but disappearance of strain 29 still took place. It is suggested that protoplasm of strain 15 can eliminate nuclei of strain 29, but that strain 29 has little or no ability to tolerate or eliminate nuclei of strain 15.