The Ebola viral disease with high fatality ratio is making a comeback in the Democratic Republic of Congo (DRC), after its rampage in West Africa in2014-16, that has spawned fears of leading to a pandemic. Vaccines such as the experimental rVSV-ZEBOV has provided protection in 70-80% of the cases, but such vaccines are in short supply and doubts exist of its availability and sustainability in pandemic cases.

Peptide vaccines promise to amend this lacunae as a chemical construct that can be scaled up to requirement in manufacturing set-up, are easy to produce in pure form and store as well as transport much more easily and economically than traditional vaccines. Although no peptide vaccines have been licensed yet for human use, the rapid growth of applications of in silica approaches to peptide vaccine design and application to a myriad of virus infections, and subsequent follow-up experimental work, have led to expectations to licensures in the near future. We have proposed a protocol to automate the search procedure for suitable vaccines using mathematical and computational modelling approaches that ensure long life of such vaccines even in the face of rapid mutational changes in viral sequences. In this paper we outline the mathematical model we have used and the recent improvements in the techniques to ensure the best recommendations for peptide vaccine libraries, especially against the Ebola virus that threatens to spill over the Congo border and cause epidemic and pandemics in a globalized world.

The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of phytotoxicity effects of chemical compounds on the Lactuca sativa seeds germination. A database of 73 compounds, assayed against L. sativa and Dragon’s molecular descriptors are used to obtain a QSAR model for the prediction of the phytotoxicity. The model is carried out with QSARINS software and validated according to OECD principles. The best model showed good value for the determination coefficient (R2 = 0.917) and others parameters appropriate for fitting (s = 0.256 and RMSEtr= 0.236). The validation results confirmed that the model has good robustness and stability (Q2LOO = 0.874 and Q2LMO= 0.875), an excellent predictive power (R2ext = 0.896) and was product of a non-random correlation (R2Y-scr = 0.130 and Q2Y-scr = -0.265). Finally, we can say that this model is a good predictor tool to predict the toxicity over L. sativa of chemical compounds.

Waste cooking oil from the food industry, restaurants/food service establishments, and households is a major environmental and ecological problem. The present work analyzed the technical and economic viability of three strategies for the use of waste cooking oil (WCO) in the gastronomic establishments of the “Obrero-Puyo” neighborhood, Province of Pastaza. The strategies analyzed were collection and sale to authorized managers, soaps and candles manufacture as possible alternatives for the WCO use. According to the economic evaluation results, candle making is the most economically profitable option with a current value of $447530.01, a return rate of 106% and a recovery period of 0.7 years. Finally, it is recommended that this analysis be extended to other neighborhoods and sectors of the Puyo city, in order to know the generation of the city and integrate the other economic units in a project of greater scope.

Reverse transcriptase is an enzyme whose function is to synthesize double-stranded DNA using the single-stranded RNA of HIV as the template. Antiretroviral drugs are effective against HIV infection because they reduce virus replication and slow the progression of the disease, even though it does not mean a definitive cure. In addition, existing drugs present a large number of adverse reactions, so the search for new antiretroviral drugs continues to be a major challenge today. In this study, a series of 107 experimentally tested 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio) thymine (HEPT) derivatives were used against HIV-I reverse transcriptase to model antiretroviral activity using molecular descriptors of DRAGON. Subsequently, a mathematical model of Multiple Linear Regression, implemented in the QSARINS software, was developed by common least squares and genetic algorithm for the variables selection, with a good performance of its parameters. The model is extensively validated in accordance with OECD regulations so that its robustness (R²=0.84), stability (Q²_LOO=0.81; Q²_LMO=0.80), low correlation of the descriptors (K_XX=0.58) and good predictive power (R²_EXT=0.85). In addition, it was found that the fit of the model is not a product of a random correlation (R²_Y-scr=0.06; Q²_Y-scr=-0.09), so it was used to predict the antiretroviral activity of eight compounds obtained by rational drug design.

Retinoblastoma is a pediatric malignant tumor, common in children up to 5 years old. It is a disease commonly developed from retinoblasts, therefore the eye presents as the primary symptom leukocoria (white reflex that occurs when the retina is exposed) to this signal occurs due to displacement of the retina caused by tumor growth. The disease can affect only one eye (unilateral) or both eyes (bilateral). Depending on the region in which the tumor develops, the optic nerve and CNS may be compromised. Phenylpropanoids are widely studied anti-tumor bioactives in medicinal chemistry, which are present in several studies with good results against brain, breast, prostate and other tumors. This research aims to present, through in silico tools, bioactive with antitumor profile for retinoblastoma of 3,4,5-trihydroxycinnamic acid derivatives. For this, 128 derivatives were designed in ChemAxon © Marvin Sketch 18.21 program to obtain their 2D structures, then were imported into HyperChemTM 8.0.6 program (RMS 0.1kcal.mol-1 in 600 cycles) for the structures to have their structures. energies minimized by molecular mechanics (MM +) and semi-empirical method (AM1). A prediction model of biological activity was performed by the KNIME Analytics Platform 3.6, using molecules contained in the chemical structure database (ChEMBL, https://www.ebi.ac.uk/chembl) with known IC50 for proteins involved with the disease. Thus, other pharmaco-chemical parameters were also analyzed, such as ligand-receptor interaction through molecular docking, absorption rate, cytotoxicity risk prediction and CPCA chemometric analysis in the Volsurf + program to identify the molecular characteristics that best explain antitumor action. . We concluded that it was possible to elect 10 promising bioactive derivatives from the series worked in this research.

Essential oils are mixtures of secondary metabolites which can be used as additives for food, cosmetic and pharmaceutical industry. Hydro-distillation technique is one of the most common extraction process but optimization studies are quite uncommon. The present study performed a general mass balance concerning the hydro-distillation of Cymbopogon citratus oil in order to determine the input and output currents. the following solute (leaves)-solvent (water) relationships (g/g) were defined: 50-200; 100-200; 150-200; 200-200; 250-200; 300-200. The greatest amount of oil and the lowest decrease in yield was performed with the following solute/solvent ratio: 200/200 (g/g), obtaining an amount of 1.7 mg of oil and a yield of 1 mg oil/leaves. The present study suggests increasing solute/solvent ratio investigation in order to optimize hydro-destillation process.

The objective of this work was to evaluate the efficacy of four native isolates of Metarhizium spp., in the control of adults of Metamasius hemipterus in laboratory conditions. A completely randomized design with seven treatments and five repetitions was used. The treatments were the four native isolates (TI6301, TS6304, PS5002, PS5003; at a concentration of 1 x10⁸ conidia.mL^-1), Chemical (Engeo at a dose of 1mL.L-1 water), a commercial biological (Micosplag at a dose of 0.5 g.L^-1 of water) and a control treatment with sterile distilled water. The treatments were applied by immersion. Mortality assessment was recorded at 5, 10, and 15 days after treatment application. Abbott's formula was used for the correction of mortality. To determine the confirmed mortality, dead adults were conditioned in humid chambers to verify the presence of mycelium on dead insects. The data was processed by ANOVA, the comparison of means was made with the Tukey test (P <0.05). The chemical treatment showed an immediate response in adults of M. hemipterus with a 100% mortality efficiency before the first 24 hours, while the native isolates began to reflect mortalities from the second day. The native isolates of Metarhizium spp. TI6301, TS6304 and PS5002 caused accumulated and corrected mortalities above 70%, and Micosplag treatment reached an efficiency of 4.17%. Confirmed mortalities were between 72.4 and 76% with native isolates TS6304 and TI6301, respectively on adults of M. hemipterus.

Certain gas sensing applications such as breath analyzers and food spoilage detection sensors require rapid step response to the target gases. However, the response time of semiconductor gas sensors is in a few to several minutes. In order to reduce the response time, we implemented an approach of early prediction in which the initial response data (first 30 seconds data) was compared with pre-defined output at different concentrations. Finally, the concentration corresponding to the pre-defined output which has less deviation with initial response data was determined as the concentration of the exposed gas. Though this method cannot predict the concentration of the target gas exactly, it can be used to identify the range of concentrations with much accuracy. By measuring the response of the sensor to exposure of combination of different gases, this technique can be utilized in identifying the multiple gases in the environment simultaneously with reasonable accuracy that is sufficient for many practical applications.

The toxic gases released by industries and other sources have a significant impact on humans and other life on the earth. Exposure to these gases at higher concentration may cause severe health issues and may even lead to death. Thus, the rapid detection of hazardous gases in the environment with high sensitivity is crucial to save the lives. However, the low sensitivity of the existing sensors limits their usage in detecting toxic gases in the air. To address this, we report a highly sensitive Hydrogen Sulfide (H₂S) gas sensor based on 2D Zinc Oxide (ZnO) nanostructures. H₂S is a poisonous and flammable gas and as per American Conference of Government Industrial Hygienists, the acceptable limit of H₂S in the air is 10 ppm. When the concentration exceeds 10 ppm, the human nose loses the ability to detect H₂S, which causes disastrous effects. The proposed sensor was tested in the range of 0.5-4 ppm H₂S and it exhibited a response of 750% upon exposure of 4 ppm H₂S. The response and recovery times are < 250 seconds and <430 seconds respectively in the tested range of concentrations of target gas.

Any substance capable of improving the efficiency, absorption and distribution of nutrients when applied in plants is considered as biostimulant, where we can include nanoprticles and nanomaterials, which, as referenced in the article Nanoparticles and nanomaterials as biostimulants of plants of the author A Juárez Maldorado, having high density of surface charges can interact in a specific way as well as non-specific with the cell surfaces, being the case of Nanoparticles and pristine nanomaterials, functionalized and with crown, crown formed by the interaction with the soil, water and the same plant itself. The magnitude and extent of the interaction will depend on the size, characteristics and substances attached to the crown, which together with the impact on the electrical potentials of the external and internal surfaces of the membrane caused by eletrostatic disturbance, modify the action of Integral membrane proteins.