Eduardo Rodríguez de San Miguel

Heliopsis longipes, commonly known as chilcuague, is a Mexican medicinal plant recognized for its diverse biological activities, largely attributed to its alkamide content, particularly affinin. However, metabolic variations associated with plant development remain poorly understood. This study evaluated the influence of phenological stage on the phytochemical profile and vasodilatory activity of H. longipes roots. Dichloromethane root extracts from plants at different developmental stages were analyzed using metabolomics based on ¹H NMR spectroscopy, complemented by GC–MS profiling. Major alkamides were isolated and structurally characterized as analytical standards. Notably, three alkamides, N-isobutylundeca-2(E)-en-8,10-diynamide, N-isobutylundeca-3(E)-en-8,10-diynamide, and N-isobutyl-2(E),4(Z)-undecadiene-8,10-diynamide, are reported for the first time in H. longipes roots. Multivariate analyses (PCA and OPLS-DA) revealed significant stage-dependent metabolic variation, particularly in affinin. The lack of correlation between valine decarboxylase activity and affinin levels suggests additional regulatory steps in its biosynthesis. Vasodilatory activity increased during development, reaching maximum effect during fructification and defoliation stages, with no significant differences between them. These findings highlight the impact of phenological stage on alkamide production and bioactivity, providing a basis for optimizing cultivation and harvest timing.

The hydrocoral Millepora complanata (fire coral) plays a critical role in reef structure and relies on a symbiotic relationship with Symbiodiniaceae algae. Environmental stressors derived from climate change, such as UV radiation and elevated temperatures, disrupt this symbiosis, leading to bleaching and threatening reef survival. To gain insight into the thermal stress response of this reef-building hydrocoral, this study investigates the proteomic response of M. complanata to bleaching during the 2015–2016 El Niño event. Fragments from non-bleached and bleached colonies of the hydrocoral M. complanata were collected from a coral reef in the Mexican Caribbean, and proteomic extracts were analyzed using nano-liquid chromatography–tandem mass spectrometry (nano-LC-MS/MS). Uni- and multivariate analyses were applied to identify significant differences in protein abundance. A total of 52 proteins showed differential abundance, including 24 that showed increased expression and 28 whose expression decreased in bleached fragments. Differentially abundant proteins were associated with amino acid biosynthesis, carbohydrate metabolism, cytoskeleton organization, DNA repair, extracellular matrix composition, redox homeostasis, and protein modification. These molecular alterations reflect critical physiological adaptations that may influence stress sensitivity or tolerance in hydrocorals. The findings indicate that heat stress induces molecular responses involving protein refolding, enhanced vesicular transport, cytoskeletal reorganization, and modulation of redox activity. This contributes to a deeper understanding of the molecular mechanisms underlying bleaching in reef-building hydrozoans and broadens current knowledge beyond the more extensively studied anthozoan corals.

A partial least squares (PLS) quantitative chemometric method based on the analysis of the mid-Fourier transform infrared spectroscopy (MID-FTIR) spectrum of polymer inclusion membranes (PIMs) used for the extraction of Cr(VI) from aqueous media is developed. The system previously optimized considering the variables membrane composition, extraction time, and pH, is characterized in terms of its adsorption isotherm, distribution coefficient, extraction percent, and enrichment factor. A Langmuir-type adsorption behavior with K_L = 2199 cm³/mmol, q_max = 0.188 mmol/g, and 0 < R_L < 1 indicates that metal adsorption is favorable. The characterization of the extraction reaction is performed as well, showing a 1:1 Cr(VI):Aliquat 336 ratio, in agreement with solvent extraction data. The principal component analysis (PCA) of the PIMs reveals a complex pattern, which is satisfactorily simplified and related to Cr(VI) concentrations through the use of a variable selection method (iPLS) in which the bands in the ranges 3451–3500 cm⁻¹ and 3751–3800 cm⁻¹ are chosen. The final PLS model, including the 100 wavelengths selected by iPLS and 10 latent variables, shows excellent parameter values with root mean square error of calibration (RMSEC) of 3.73115, root mean square error of cross-validation (RMSECV) of 6.82685, bias of −1.91847 × 10⁻¹³, cross-validation (CV) bias of 0.185947, R² Cal of 0.98145, R² CV of 0.940902, recovery% of 104.02 ± 4.12 (α = 0.05), sensitivity% of 0.001547 ppb, analytical sensitivity (γ) of 3.8 ppb, γ⁻¹: 0.6 ppb⁻¹, selectivity of 0.0155, linear range of 5.8–100 ppb, limit of detection (LD) of 1.9 ppb, and limit of quantitation (LQ) of 5.8 ppb. The developed PIM sensor is easy to implement as it requires few manipulations and a reduced number of chemical compounds in comparison to other similar reported systems.

Wine is a temperature, light, and oxygen-sensitive product, so its physicochemical characteristics can be modified by variations in temperature and time when samples are either sampled, transported, and/or analyzed. These changes can alter its metabolomic fingerprinting, impacting further classification tasks and quality/quantitative analyses. For these reasons, the aim of this work is to compare and analyze the information obtained by different chemometric methods used in a complementary form (PCA, ASCA, and PARAFAC) to study ¹H-NMR spectra variations of four red wine samples kept at different temperatures and time lapses. In conjunction, distinctive changes in the spectra are satisfactorily tracked with each chemometric method. The chemometric analyses reveal variations related to the wine sample, temperature, and time, as well as the interactions among these factors. Moreover, the magnitude and statistical significance of the effects are satisfactorily accounted for by ASCA, while the time-related effects variations are encountered by PARAFAC modeling. Acetaldehyde, formic acid, polyphenols, carbohydrates, lactic acid, ethyl lactate, methanol, choline, succinic acid, proline, acetoin, acetic acid, 1,3-propanediol, isopentanol, and some amino acids are identified as some of the metabolites which present the most important variations.

A partial least squares (PLS) quantitative chemometric method based on the analysis of the MID-FTIR spectrum of polymer inclusion membranes (PIMs) used for the extraction of Cr(VI) from aqueous media is developed. The system previously optimized considering the variables membrane composition, extraction time, and pH, is characterized in terms of its adsorption isotherm, distribution coefficient, extraction percent and enrichment factor. A Langmuir type adsorption behavior with KL = 21.99 L/mg, qmax = 0.242 mmol/g and 0<RL<1, indicates that metal adsorption is favorable. The characterization of the extraction reaction is performed as well showing an 1:1 Cr(VI):Aliquat 336 ratio, in agreement with solvent extraction data. The principal component analysis (PCA) of the PIMs revels a complex pattern, which is satisfactorily simplified and related to Cr(VI) concentrations through the use of a variable selection method (iPLS) in which bands in the ranges 3451–3500 cm-1 and 3751–3800 cm-1 are chosen. The final PLS model including the 100 wavelengths selected by iPLS and 10 latent variables shows excellent parameter values with RMSEC: 3.73115, RMSECV: 6.82685, Bias: -1.91847e-13, CV Bias: 0.185947, R2 Cal: 0.98145, R2 CV: 0.940902, recovery%: 104.02 ± 4.12 (=0.05), sensitivity%: 0.001547 ppb, γ: 3.8 ppb, γ- 1: 0.6 ppb-1, selectivity: 0.0155, linear range: 5.8–100 ppb, LD: 1.9 ppb, and LQ: 5.8 ppb. The developed PIM sensor is easy to implement as it requires few manipulations and reduced number of chemical compounds in comparison to other similar reported systems.

The synthesis and optimization of polymeric inclusion membranes (PIMs) for the transport of Cd(II) and Pb(II) and their separation from Zn(II) in aqueous saline media are presented. The effects of NaCl concentrations, pH, matrix nature, and metal ion concentrations in the feed phase are additionally analyzed. Experimental design strategies were used for the optimization of PIM composition and evaluating competitive transport. Synthetic seawater with 35% salinity, commercial seawater collected from the Gulf of California (Panakos^®), and seawater collected from the beach of Tecolutla, Veracruz, Mexico, were employed. The results show an excellent separation behavior in a three-compartment setup using two different PIMs (Aliquat 336 and D2EHPA as carriers, respectively), with the feed phase placed in the central compartment and two different stripping phases placed on both sides: one solution with 0.1 mol/dm³ HCl + 0.1 mol/dm³ NaCl and the other with 0.1 mol/dm³ HNO₃. The selective separation of Pb(II), Cd(II), and Zn(II) from seawater shows separation factors whose values depend on the composition of the seawater media (metal ion concentrations and matrix composition). The PIM system allows S(Cd) and S(Pb)~1000 and 10 < S(Zn) < 1000, depending on the nature of the sample. However, values as high as 10,000 were observed in some experiments, allowing an adequate separation of the metal ions. Analyses of the separation factors in the different compartments in terms of the pertraction mechanism of the metal ions, PIMs stabilities, and preconcentration characteristics of the system are performed as well. A satisfactory preconcentration of the metal ions was observed after each recycling cycle.

Polymer inclusion membranes (PIMs) are developed to be used as colorimetric sensors for the simultaneous determination and quantification of Cu(II), Zn(II), Pb(II) from aqueous solutions using chemometric methods. Different physical and chemical factors that influence the detection process of the analytes are studied, i.e., the concentration of the metal cation, the amount of membrane, and the pH of the solution. The most significant variables within the detection process in membrane sensors are those that are closely related to the chemical reaction of the detection, that is, the concentration of the metal cation and the number of active sites available in the optomembrane. The reversibility and durability of the signal are evaluated as well. The optomembrane reaches 95% of the optical signal attributed to the process of formation of the different colorful complexes in 20 min, regardless of the metal cation. The optomembrane of CTA—TEHP—PAN presents a very narrow linear interval of response to the concentration of the cations, Zn(II) and Cu(II) ranging from 0.6 to 6 ppm; for higher concentrations the polymeric detector presents saturation. The response of the sensor to different concentrations of Pb(II) is not linear, which can be attributed to the lack of chemical affinity to generate the complex in the polymer film. The simultaneous determination of the three metal cations by three chemometric methods [multivariate curve resolution (MCR), artificial neural networks (ANNs) and partial least squares (PLS)] is performed with an experimental central composite design matrix at five levels and three experimental factors. The construction of the quantification model is carried out from the information obtained from the VIS spectrum of the PIMs exposed to the aqueous solutions. The predictive power of the quantification models for each of the metal cations is evaluated contemplating the determination coefficient (R²) and the root mean square error (RMSE) values. Results favors the use of the PLS algorithm, although due to the competition for the actives sites of the chromophore, Pb(II) determination is not satisfactorily acomplished. Principal component analysis (PCA) is in addition employed to visualize patterns in the synthesized membranes.

Preterm newborns are extremely vulnerable to morbidities, complications, and death. Preterm birth is a global public health problem due to its socioeconomic burden. Nurturing preterm newborns is a critical medical issue because they have limited nutrient stores and it is difficult to establish enteral feeding, which leads to inadequate growth frequently associated with poor neurodevelopmental outcomes. Parenteral nutrition (PN) provides nutrients to preterm newborns, but its biochemical effects are not completely known. To study the effect of PN treatment on preterm newborns, an untargeted metabolomic ¹H nuclear magnetic resonance (NMR) assay was performed on 107 urine samples from 34 hospitalized patients. Multivariate data (Principal Component Analysis, PCA, Orthogonal partial least squares discriminant analysis OPLS-DA, parallel factor analysis PARAFAC-2) and univariate analyses were used to identify the association of specific spectral data with different nutritional types (NTs) and gestational ages. Our results revealed changes in the metabolic profile related to the NT, with the tricarboxylic acid cycle and galactose metabolic pathways being the most impacted pathways. Low citrate and succinate levels, despite higher glucose relative urinary concentrations, seem to constitute the metabolic profile found in the studied critically ill preterm newborns who received PN, indicating an energetic dysfunction that must be taken into account for better nutritional management.

Polymer inclusion membranes (PIMs) are a kind of membrane in which a carrier is physically trapped within a polymer network usually in, but not restricted to, the presence of a plasticizer