Iron nanoparticles synthesized using green methods with native plant extracts exhibit beneficial physicochemical properties. This synthesis method is an effective and sustainable alternative for treating heavy metal-contaminated water. In this study, the lead removal capacity of iron nanoparticles produced through green synthesis, employing Condaliopsis obtrusively extract as a stabilizing agent, was evaluated. Synthesis was conducted by varying the initial concentration of ferric chloride (0.75 M, 0.125 M) and pH (8, 11). The coprecipitation method was used to produce magnetite nanoparticles, and the morphological characterization was conducted by scanning electron microscopy (SEM) and atomic force microscopy (AFM), yielding diameters ranging from 20 to 40 nm. This synthesis approach resulted in a 41.5% yield, providing 1.2 g of purified nanoparticles per batch from an initial volume of 50 mL A superficial area of 105.47 m2/g was calculated using the Brunauer-Emmet-Teller (BET) method, indicating a mesoporous structure. Based on the results, the optimal conditions for nanoparticle synthesis are an iron concentration of 0.75 M and a pH of 11. The adsorption tests showed a removal percentage of 99% for Pb 2+, indicating that the nanoparticles are suitable for water remediation
Este estudio evaluó la eficacia de diferentes dispositivos para la vitrificación de embriones bovinos producidos in vitro, comparando sistemas abiertos y cerrados en términos de supervivencia y calidad embrionaria. Se analizaron 761 ovocitos bovinos procedentes de matadero, que fueron madurados, fecundados y cultivados en condiciones in vitro hasta el estadio de blastocisto y vitrificados en los siguientes dispositivos: Cryotop, OPS, Cryotip y CVM. La supervivencia se midió mediante la reexpansión del blastocele y la eclosión a las 48 h post-vitrificación. La reexpansión del blastocele fue similar entre los dispositivos: CVM (90,36%), Cryotip (87,11%), Cryotop (91,10%) y OPS (90,61%), sin diferencias significativas (p≥0,05), la tasa de eclosión mostró diferencias significativas (p≤0,05): Cryotop (85,63%) y OPS (85,37%) superaron a Cryotip (78,70%), mientras que CVM presentó un valor intermedio (82,60%). El índice de apoptosis no mostró diferencias significativas entre los dispositivos: CVM (2,63%), Cryotip (2,27%), Cryotop (2,46%) y OPS (2,25%) (p≥0,05). Tanto los sistemas abiertos como los cerrados son eficaces para preservar la viabilidad de los embriones bovinos; la elección del sistema puede depender de factores prácticos y económicos, ya que todos mantuvieron una calidad embrionaria comparable, lo que reafirma la importancia de optimizar los protocolos para mejorar la crioconservación en biotecnología reproductiva.
No existen estudios sobre el valor nutricional y fitoquímico del fruto de Isolatocereus dumortieri. El objetivo de este estudio fue evaluar el valor nutricional y nutracéutico del fruto de I. dumortieri recolectado en Naxthéy, Ixmiquilpan, Hidalgo, México. Se realizó la caracterización ecológica y edáfica de los sitios de recolección. Los frutos fueron cosechados aleatoriamente en estado de madurez de consumo, para determinar sus características nutricionales y compuestos antioxidantes. Esta cactácea crece en matorrales desértico aluviales, sin actividad antrópica directa. Los frutos presentaron un alto contenido de carbohidratos, fibra, proteína, potasio, magnesio y cobre en comparación con otras cactáceas comerciales. Además, podrían ser usados como una fuente potencial de compuestos nutracéuticos por su alto contenido de betalaínas (16.16 mg/100 g) y compuestos fenólicos (290.23 mg de EAG/100 g). Se encontró alta actividad antioxidante en los frutos, la técnica FRAP reportó 37.59 mM de equivalentes de Trolox (ET) por 100 g de pulpa fresca (p.f.), mientras que los ensayos de eliminación de radicales ABTS y DPPH reportaron 31.14 y 21.70 mM de ET/100 g, respectivamente. En conclusión, los frutos de I. dumortieri son una promisoria fuente de nutracéuticos y podrían ser empleados en la formulación de alimentos funcionales.
Soil salinity threatens agricultural productivity, especially in regions such as La Ciénega de Chapala, Michoacán, where salinity problems generate important economic losses. In this study, 100 hectares of bare soil were evaluated in the municipality of Villamar, Michoacán, to identify the ionic composition and classify the soil according to different salinity indices. A simple random sampling was performed, and the following chemical parameters were determined in the saturation paste extract: Ca2+, Mg2+, Na+, K+, CO32-, HCO3-, Cl-, SO42-, pH, electrical conductivity (EC), evaporated dry residue, and calcined dry residue. EC, Sodium Adsorption Ratio (SAR), and Exchangeable Sodium Percent (ESP) were used for classification. Spatial interpolation maps using triangulated irregular networks (TIN) allowed visualization of the distribution of both ESP and SAR. The predominant ions were Na+ and SO42-, with 21.45 and 15.83 mEq/L, respectively. EC was positively correlated with Total Dissolved Solids, and the ionic strength was high. Between 50 and 60% of the samples were classified as non-sodium. High spatial heterogeneity was identified, 43% of the property was classified as high in salinity, low in sodium, however, the southern zone is the most affected.
Pulsed Electrochemical Machining (PECM) is an advanced manufacturing method used in the metalworking industry to manufacture metal tools or components utilizing the principle of electrolysis. As a result, chemical and electrical phenomena of different natures are involved, making it difficult to describe the behavior that governs material wear accurately. An approach known as ANFIS (Adaptive Neuro Fuzzy Inference System) was employed to address this issue, integrating two artificial intelligence techniques: artificial neural networks and fuzzy logic. This algorithm performs inference-based mapping using fuzzy logic while adaptively adjusting parameters through a supervised criterion, as in neural networks. For this purpose, experimental data from electrochemical machining divided into subsets were used to train and test the model. In this way, a root mean square error in the prediction of the material removal rate of 0.394 and a coefficient of determination of 0.845 were obtained. Finally, the analysis of the residuals allowed to exclude the presence of heteroscedasticity, confirming an adequate predictive performance without bias and with constant variance according to the Breusch-Pagan statistical test criterion
