Autonomous University of San Luis Potosí

Mining activities can significantly alter surface and groundwater systems. Therefore, sustainable water resources management has become a central requirement and strategic necessity for responsible mining. This requires tools capable of characterizing water sources, flow paths, and contaminant dynamics to support informed and responsible decision-making. Stable and radioactive isotopes are powerful tracers of the origin, age, movement, and transport of water and its constituents, as well as indicators of the water-rock interactions affecting groundwater and surface water quality. This paper reviews publications from 2022 to 2024 that discuss advancements in isotopic techniques and their applications, with the goal to promote the adoption of integrated isotopic and geochemical methods in mining-related assessments. The review is organized into three sections: 1) the understanding of hydro(geo)logical circuits: water sources and circulation, mixing processes, hydro(geo)logical alteration, river-groundwater interactions and groundwater age; 2) the assessment of mining-related contamination processes: contamination by S or by N compounds, discrimination between mining and other contamination sources, the use of minor and trace element isotopes, the salinity issues, and the identification of gas production and exchange; and 3) the application of isotope approaches for monitoring the impact of mining and assessing remediation measures, whether natural or engineered. Finally, the intrinsic strengths and weaknesses, as well as the external opportunities and limitations to the application of isotopic approaches are discussed. The review summarizes the commonly encountered sources and processes in mining settings and provides graphical outputs to assist with interpreting new experimental data, highlighting environmental isotopes as “sustainable investigation tools”. • Isotopic approaches in mining-related settings are assessed with a SWOT analysis • Graphical outputs to assist with interpreting new experimental data are provided • Environmental isotopes represent fully-fledged “sustainable investigation tools”

The development of analytical approaches capable of detecting subtle protein conformational changes is of significant interest in biomedicine, particularly for disease diagnostics and biomolecular characterization. In this work, the tumor suppressor p53 protein was selected as a model system to evaluate an analytical platform based on Raman spectroscopy combined with surface-enhanced Raman spectroscopy (SERS) and supervised machine learning for the classification of closely related protein variants. Label-free Raman and SERS spectra of recombinant wild-type p53 and its hotspot mutants R175H and R273H were acquired on bare Al and Al coated with gold nanospheres, gold nanorods, and silver nanoparticles. Principal Component Analysis (PCA) revealed distinct spectral fingerprints among the p53 variants, with relevant contributions in the amide III and CH stretching regions, indicating subtle conformational differences. Supervised classification was performed using several machine learning algorithms under a nested, group-disjoint cross-validation protocol (holding out entire acquisition lines) to account for within-line spectral correlation. Among tested models, a linear Support Vector Machine (Linear-SVM) achieved the highest performance, reaching an accuracy of 92.9±6.9% on AuNS@Al substrates. These results demonstrate that the integration of optimized nanostructured SERS substrates, Raman spectroscopy, and machine learning constitutes a robust analytical platform for the structural classification of wild-type and mutant p53 proteins. The proposed approach provides a versatile framework for studying conformational changes in biomolecules of biomedical relevance and supports its potential application in cancer biomarker detection and protein misfolding studies.

Cocoa pod husk (CPH), a major agro-industrial residue, contains valuable bioactive compounds whose recovery can support sustainable waste valorization. This study evaluated the influence of increasing ethanol concentrations on the ultrasound-assisted extraction (UAE) of bioactive compounds from CPH and their antioxidant, antihypertensive, and antihyperglycemic activity. Dried and milled CPH was extracted using ethanol–water mixtures (0–100% ethanol) under fixed ultrasonic conditions. Cocoa pod husk powder characterization and the resulting extracts were analyzed in terms of chemical composition (lignocellulosic compounds, proximate and elemental composition, and bromatological composition), antioxidant capacity, and in vivo antihypertensive and antihyperglycemic effects in Wistar rats. The results showed that solvent polarity strongly modulated extraction efficiency: absolute ethanol yielded the highest phenolic (171.43 mg GAE/g) and flavonoid (132.05 mg QE/g) content, whereas hydroalcoholic mixtures, particularly 50:50, enhanced overall antioxidant performance, especially in FRAP. The chemical analysis results showed the selective recovery of compounds such as quercetin, hesperidin, and theobromine, and FTIR-PCA results revealed distinct solvent-dependent chemical profiles. In vivo assays indicated modest blood pressure stabilization and a more pronounced antihyperglycemic effect after chronic administration. Overall, UAE proved an effective, rapid, and solvent-efficient method for CPH valorization, highlighting its potential for producing natural antioxidants applicable to food, nutraceutical, and cosmetic formulations.

Efficient conversion of mid-infrared (MIR) radiation into electricity remains a challenge for thermoelectric devices. We present multiresonant Ag–Si:B–Ni bowtie cross nanoantenna (BCN) arrays that exploit plasmon-enhanced photothermal effects to achieve broadband MIR absorption and voltage generation via the Seebeck effect. The 9×9 BCN arrays, fabricated by electron beam lithography, exhibit multiple plasmonic resonances from 18 to 48 THz with a ∼30 THz bandwidth. COMSOL simulations reveal strong field confinement and open-circuit voltages up to 11.19 μV under 1000 W·m2 illumination, which are experimentally validated by Fourier Transform Infrared measurements. The broadband response, geometry-dependent tunability, and efficient heat-to-electric conversion establish BCNs as promising candidates for waste-heat harvesting, MIR sensing, and plasmonic metasurface thermoelectrics.

Background/Objectives: Mexicans are disproportionately affected by dyslipidemia, specifically low high-density lipoprotein (HDL-C) and high triglyceride (TG) concentrations. Research on the genetic contributions to dyslipidemia, conducted primarily among European populations, has identified numerous single-nucleotide polymorphisms (SNPs) with small effect sizes and low replication rates. A genetic risk score (GRS) can examine the cumulative effects of multiple SNPs and potentially explain greater phenotypic variability than individual SNPs. GRS in Mexican populations and those without diagnosed dyslipidemia are limited. This study aims to construct a GRS from lipid metabolism-related SNPs and determine its associations with blood lipid concentrations in young Mexican college students. Methods: Adults (ages 18-25 years, n = 580) provided a fasting blood sample to determine TG and HDL-C concentrations. DNA was genotyped for 14 SNPs in lipid metabolism pathways (reverse cholesterol transport [RCT], cellular lipid uptake, and lipoprotein formation and transport). Additive (number of risk alleles) and weighted (regression-derived β coefficients) GRS were calculated for individual pathways, and their sum (total GRS) was explored. Associations among individual SNPs, GRS, and blood lipids were determined through general linear models in SAS. Results: The additive RCT and total GRS were associated with TG (both p < 0.05). The RCT pathway explained 3.4% of the variability in TG concentrations, and the total GRS explained 6.1%. The weighted RCT GRS was associated with HDL-C (p = 0.007). The ATP-binding cassette protein (ABCA1) rs9282541 variant was most strongly associated with HDL-C (p = 0.016). When this SNP was removed from the GRS, the association became non-significant. Conclusions: SNPs in lipoprotein metabolism pathways cumulatively associate with blood lipid concentrations in young Mexican adults. The ABCA1-rs9282541 variant, previously shown to be positively associated with low HDL-C concentrations in Amerindian populations, had the strongest association with HDL-C. Further work is needed to elucidate the roles of genetic admixture and lifestyle risk factors in dyslipidemia in this population.

El greenwashing se ha consolidado como una práctica recurrente en la industria y en la iniciativa privada, al utilizar discursos de sustentabilidad que no siempre corresponden a transformaciones reales orientadas a la protección ambiental y animal. Desde la perspectiva de la Criminología Verde, estas prácticas pueden contribuir indirectamente a la persistencia del daño ambiental y a la evasión de responsabilidades empresariales. El objetivo de este estudio es proponer un modelo preventivo del crimen ambiental y animal aplicable a la industria y a la iniciativa privada, orientado a reducir la probabilidad de prácticas de greenwashing antes de la materialización del daño ambiental. La investigación adopta un enfoque cualitativo con un diseño teórico-documental de carácter analítico-propositivo, basado en el análisis sistemático de literatura científica, marcos normativos, estándares internacionales, certificaciones ambientales y documentación institucional, así como en la revisión de casos documentados de malas prácticas corporativas. A partir de este análisis se identifican patrones de riesgo y categorías analíticas que permiten estructurar un modelo preventivo centrado en el desarrollo sustentable, la gobernanza verde, la responsabilidad social empresarial y la verificación de prácticas sustentables. Los resultados muestran que la prevención del greenwashing en la industria y la iniciativa privada requiere mecanismos integrales que articulen regulación, control organizacional y transparencia. Se concluye que el modelo propuesto constituye una herramienta conceptual útil para fortalecer la prevención del crimen ambiental y animal, promoviendo prácticas empresariales coherentes con el desarrollo sustentable y los objetivos de la Agenda 2030.