Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network

An appropriate calibration and forecasting of volatility and market risk are some of the main challenges faced by companies that have to manage the uncertainty inherent to their investments or funding opera- tions such as banks, pension funds or insurance companies. This has become even more evident after the 2007-2008 Financial Crisis, when the forecasting models assessing the market risk and volatility failed. Since then, a significant number of theoretical developments and methodologies have appeared to im- prove the accuracy of the volatility forecasts and market risk assessments. Following this line of thinking, this paper introduces a model based on using a set of Machine Learning techniques, such as Gradient Descent Boosting, Random Forest, Support Vector Machine and Artificial Neural Network, where those al- gorithms are stacked to predict S&P500 volatility. The results suggest that our construction outperforms other habitual models on the ability to forecast the level of volatility, leading to a more accurate assess- ment of the market ris

Mack-net model: Blending Mack's model with Recurrent Neural Networks

In general insurance companies, a correct estimation of liabilities plays a key role due to its impact on management and investing decisions. Since the Financial Crisis of 2007?2008 and the strengthening of regulation, the focus is not only on the total reserve but also on its variability, which is an indicator of the risk assumed by the company. Thus, measures that relate profitability with risk are crucial in order to understand the financial position of insurance firms. Taking advantage of the increasing computational power, this paper introduces a stochastic reserving model whose aim is to improve the performance of the traditional Mack?s reserving model by applying an ensemble of Recurrent Neural Networks. The results demonstrate that blending traditional reserving models with deep and machine learning techniques leads to a more accurate assessment of general insurance liabilities

Stochastic reserving with a stacked model based on a hybridized Artificial Neural Network

Currently, legal requirements demand that insurance companies increase their emphasis on monitoring the risks linked to the underwriting and asset management activities. Regarding underwriting risks, the main uncertainties that insurers must manage are related to the premium sufficiency to cover future claims and the adequacy of the current reserves to pay outstanding claims. Both risks are calibrated using stochastic models due to their nature. This paper introduces a reserving model based on a set of machine learning techniques such as Gradient Boosting, Random Forest and Artificial Neural Networks. These algorithms and other widely used reserving models are stacked to predict the shape of the runoff. To compute the deviation around a former prediction, a log-normal approach is combined with the suggested model. The empirical results demonstrate that the proposed methodology can be used to improve the performance of the traditional reserving techniques based on Bayesian statistics and a Chain Ladder, leading to a more accurate assessment of the reserving risk

Small molecule inhibitors of the response regulator ArsR exhibit bactericidal activity against Helicobacter pylori

Helicobacter pylori is considered the most prevalent bacterial pathogen in humans. The increasing antibiotic resistance evolved by this microorganism has raised alarm bells worldwide due to the significant reduction in the eradication rates of traditional standard therapies. A major challenge in this antibiotic resistance crisis is the identification of novel microbial targets whose inhibitors can overcome the currently circulating resistome. In the present study, we have validated the use of the essential response regulator ArsR as a novel and promising therapeutic target against H. pylori infections. A high-throughput screening of a repurposing chemical library using a fluorescence-based thermal shift assay identified several ArsR binders. At least four of these low-molecular weight compounds noticeably inhibited the DNA binding activity of ArsR and showed bactericidal effects against antibiotic-resistant strains of H. pylori. Among the ArsR inhibitors, a human secondary bile acid, lithocholic acid, quickly destroyed H. pylori cells and exhibited partial synergistic action in combination with clarithromycin or levofloxacin, while the antimicrobial effect of this compound against representative members of the normal human microbiota such as Escherichia coli and Staphylococcus epidermidis appeared irrelevant. Our results enhance the battery of novel therapeutic tools against refractory infections caused by multidrug-resistant H. pylori strains

Bioactivity, nutritional property, and rapid chemical characterization of aqueous extract of Annona muricata leaf from Mexico

Purpose: To investigate the bioactive and nutritional properties, as well as rapid chemical characterization of aqueous extract of Annona muricata leaf from Mexico Methods: The crude aqueous extract of A. muricata leaf was obtained by decoction. Cytotoxicity was tested against cervicouterine cancer cells (HeLa) using methyl thiazol tetrazolium (MTT) assay. Antioxidant activity was evaluated using 2, 2-diphenylpicrylhydrazyl (DPPH) assay. Nutritional evaluation was carried out according to Association of Official Analytical Chemists (AOAC) procedures. Rapid qualitative chemical characterization of the extract was carried out by direct analysis in real-time mass spectrometry (DART-MS) method. Results: The aqueous extract of A. muricata leaf showed cytotoxicity against HeLa cells and also antioxidant activity in a concentration-dependent manner. Nutritional analysis revealed the presence of carbohydrates, vitamin C, Na, and Fe in the aqueous extract. DART-MS spectra showed the presence of alkaloids and phenols as the major components. Conclusion: The cytotoxic and antioxidant activities of the aqueous extract of A. muricata leaf lend some support for its traditional uses as anti-cancer remedy. These activities are probably due to its active secondary metabolites. Thus, the aqueous extract is a source of healthy nutritional components as well as a potential anti-cancer agent for humans

Amelioration of cadmium-produced teratogenicity and genotoxicity in mice given Arthrospira maxima (Spirulina) treatment

Evaluation of the effects of Arthrospira maxima (AM) was made, otherwise known as Spirulina, on the teratogenicity, genotoxicity, and DNA oxidation processes induced by cadmium (Cd). Pregnant ICR mice were divided into groups and administered water, Cd only, AM only, or AM plus Cd. AM was administered orally at doses of 200, 400, and 800 mg/kg from gestational day 0 (GD0) to GD17, and at GD7 there was an intraperitoneal challenge of Cd (1.5 mg/kg). Cd only caused fetal malformations, including exencephaly, micrognathia, ablephary, microphthalmia, and clubfoot, as well as a significant increase in the quantity of micronucleated polychromatic erythrocytes (MNPE) and of micronucleated normochromatic erythrocytes (MNNE) in blood cells of both the mothers and their fetuses. An increased level of oxidation was also found, measured by a rise in the levels of the adduct 8-hydroxy-2-deoxyguanosine. In a dose-dependent manner, AM significantly reduced the number of external, visceral, and skeletal malformations, the quantity of MNPE and MNNE, and the level of DNA oxidation. The results suggest that AM may reduce the genotoxic effects and rates of congenital malformations caused by exposure to Cd in utero and that the antioxidant activity of this cyanobacterium could be responsible, at least in part, for producing this effect

Repurposing dihydropyridines for treatment of helicobacter pylori infection

Antibiotic resistance is a major cause of the increasing failures in the current eradication therapies against Helicobacter pylori. In this scenario, repurposing drugs could be a valuable strategy to fast-track novel antimicrobial agents. In the present study, we analyzed the inhibitory capability of 1, 4-dihydropyridine (DHP) antihypertensive drugs on the essential function of the H. pylori response regulator HsrA and investigated both the in vitro antimicrobial activities and the in vivo efficacy of DHP treatments against H. pylori. Six different commercially available and highly prescribed DHP drugs—namely, Nifedipine, Nicardipine, Nisoldipine, Nimodipine, Nitrendipine, and Lercanidipine—noticeably inhibited the DNA binding activity of HsrA and exhibited potent bactericidal activities against both metronidazole-and clarithromycin-resistant strains of H. pylori, with minimal inhibitory concentration (MIC) values in the range of 4 to 32 mg/L. The dynamics of the decline in the bacterial counts at 2 × MIC appeared to be correlated with the lipophilicity of the drugs, suggesting different translocation efficiencies of DHPs across the bacterial membrane. Oral treatments with 100 mg/kg/day of marketed formulations of Nimodipine or Nitrendipine in combination with omeprazole significantly reduced the H. pylori gastric colonization in mice. The results presented here support a novel therapeutic solution for treatment of antibiotic-resistant H. pylori infections

Estudio de estabilidad de tabletas que contienen 20 mg de policosanol como ingrediente activo

El objetivo de un estudio de estabilidad es determinar el período de tiempo durante el cual el producto farmacéutico conserva adecuadamente sus propiedades al ser almacenado en determinadas condiciones. El estudio de estabilidad de las tabletas que contienen 20 mg de policosanol, un nuevo medicamento con propiedades hipocolesterolemizantes, se realizó con el objetivo de predecir la fecha de vencimiento e investigar la posible aparición de productos de degradaci ón. Para ello, se observaron durante el estudio propiedades como: color, dureza, desintegración, masa promedio, contenido de policosanol y contenido de microorganismos. El contenido de ingrediente activo se determinó por cromatografía gaseosa, utilizando la técnica validada a tales efectos. También fueron estudiados los efectos de las condiciones drásticas de almacenamiento tales como: hidrólisis ácida y básica, oxidación, fotólisis y termólisis. Por otra parte, se realizaron estudios a largo plazo teniendo en cuenta dos zonas climáticas, o sea, zona II (25 °C y 60 % de humedad relativa (HR)) y la zona IV (30 °C y 70 % de HR) y un estudio acelerado a 40 °C y 75 % de HR. Estos estudios demostraron que esta formulación es estable, ya que no se produjeron cambios significativos en los indicadores estudiados según los criterios de aceptación establecidos en las condiciones estudiadas. El contenido de policosanol se mantuvo con muy poca variación durante todo el estudio, por lo que no fue posible utilizar el método cinético de Arrhenius para la determinación de la fecha de vencimiento

Metforminium Decavanadate as a Potential Metallopharmaceutical Drug for the Treatment of Diabetes Mellitus

New potential drugs based on vanadium are being developed as possible treatments for diabetes mellitus (DM) and its complications. In this regard, our working group developed metforminium decavanadate (MetfDeca), a compound with hypoglycemic and hypolipidemic properties. MetfDeca was evaluated in models of type 1 and type 2 diabetes mellitus, on male Wistar rats. Alloxan-induction was employed to produce DM1 model, while a hypercaloric-diet was employed to generate DM2 model. Two-month treatments with 3.7 μg (2.5 μM)/300 g/twice a week for DM2 and 7.18 μg (4.8 μM)/300 g/twice a week for DM1 of MetfDeca, respectively, were administered. The resulting pharmacological data showed nontoxicological effects on liver and kidney. At the same time, MetfDeca showed an improvement of carbohydrates and lipids in tissues and serum. MetfDeca treatment was better than the monotherapies with metformin for DM2 and insulin for DM1. Additionally, MetfDeca showed a protective effect on pancreatic beta cells of DM1 rats, suggesting a possible regeneration of these cells, since they recovered their insulin levels. Therefore, MetfDeca could be considered not only as an insulin-mimetic agent, but also as an insulin-enhancing agent. Efforts to elucidate the mechanism of action of this compound are now in progress

Fibers spreading worldwide: Microplastics and other anthropogenic litter in an Arctic freshwater lake

We investigated the presence of microplastics and other anthropogenic litter in the sediments adhered to rocks of an Arctic freshwater lake at Ny-Ålesund (Svalbard Archipelago, 78°N; 11°E). Most of the sampled microparticles were fibers (>90%). The identification of polymer types and additives was performed by combining three spectroscopic techniques, namely Raman Microscopy, Fourier-Transform Infrared microspectroscopy (μFTIR) and Synchrotron Radiation μFTIR (SR-FTIR). SR-FTIR confirmed the presence of poly(ethylene terephthalate) fibers, while RAMAN spectroscopy provided evidence of fibers containing industrial additives. Our results estimated an average concentration of 400 microparticles/m2 of rocks identified as anthropogenic litter, which included an estimation of 90 microplastics/m2 identified as polyester fibers; the rest are mostly natural fibers with evidence of anthropogenic origin. Taken together, the results proved the occurrence of anthropogenic pollutants in remote polar areas. Their probable origin is the long range atmospheric transpor