Antimicrobial resistance is a global health threat. Misuse and overuse of antimicrobials are the main drivers in developing drug-resistant bacteria. The emergence of the rapid global spread of multi-resistant bacteria requires urgent multisectoral action to generate novel treatment alternatives. Combination therapy offers the potential to exploit synergistic effects for enhanced antibacterial efficacy of drugs. Understanding the complex dynamics and kinetics of drug interactions in combination therapy is crucial. Therefore, this review outlines the current advances in antibiotic resistance's evolutionary and genetic dynamics in combination therapies-exposed bacteria. Moreover, we also discussed four pivotal future research areas to comprehend better the development of antibiotic resistance in bacteria treated with combination strategies.

Modeling of irrigation and agricultural drainage requires knowledge of the soil hydraulic properties. However, uncertainty in the direct measurement of the saturation moisture content (${\theta }_{\mathrm{s}}$) has been generated in several methodologies for its estimation, such as Pedotransfer Functions (PTFs) and Artificial Neuronal Networks (ANNs). In this work, eight different PTFs were developed for the (${\theta }_{\mathrm{s}}$) estimation, which relate to the proportion of sand and clay, bulk density (BD) as well as the saturated hydraulic conductivity ($K_{\mathrm{s}}$). In addition, ANNs were developed with different combinations of input and hidden layers for the estimation of ${\theta }_{\mathrm{s}}$. The results showed R${}^2$ values from $0.9046\le {\mathrm{R}}^2\le 0.9877$ for the eight different PTFs, while with the ANNs, values of R${}^2>0.9891$ were obtained. Finally, the root-mean-square error (RMSE) was obtained for each ANN configuration, with results ranging from $0.0245\le \mathrm{RMSE}\le 0.0262$. It was found that with particular soil characteristic parameters (% Clay, % Silt, % Sand, BD and $K_{\mathrm{s}}$), accurate estimate of ${\theta }_{\mathrm{s}}$ is obtained. With the development of these models (PTFs and ANNs), high R${}^2$ values were obtained for 10 of the 12 textural classes.

Several studies have assessed crop water requirements based on soil properties, but these have been on a small scale or on soils with similar textures. Here, a data base of soil measurements in the field and laboratory from sites across Irrigation District 023, San Juan del Rio, Queretaro, Mexico was sampled, collected, analyzed, and integrated. The data base, named, NaneSoil, contains information on 900 samples obtained from irrigated plots. NaneSoil cover 10 of the 12 textural classes with the following information: sand, silt, clay contents, bulk density, saturated volumetric water content, field capacity, permanent wilting point and saturated hydraulic conductivity. The aim of this work is to provide the scientific community with sufficient information to perform a large number of analyses, for example, development of pedotransfer functions, calculation of water requirements of plants in soils with similar characteristics, modeling of infiltration, optimal irrigation discharge calculation, among others. The dataset also promotes the scientific community to contribute their own measurements to further strengthen the knowledge of flow in the porous medium.

Background. Antimicrobial resistance (AMR) poses a significant global health threat, necessitating a deeper understanding of bacterial adaptation mechanisms. Introduction. This study investigates the genotypic and phenotypic evolutionary trajectories of Escherichia coli under meropenem and gentamicin selection, and it benchmarks these findings against florfenicol-evolved strains. Methodology. Utilizing a downsized, three-layer acrylic modified “Microbial Evolution and Growth Arena (MEGA-plate) system”—scaled to 40 × 50 cm for sterile handling and uniform 37 °C incubation—we tracked adaptation over 9–13 days, enabling real-time visualization of movement across antibiotic gradients. Results. Meropenem exposure elicited pronounced genetic heterogeneity and morphological remodeling (filamentous and circular forms), characteristic of SOS-mediated division arrest and DNA-damage response. In contrast, gentamicin exposure produced a uniform resistance gene profile and minimal shape changes, suggesting reliance on conserved defenses without major morphological adaptation. Comprehensive genomic analysis revealed a core resistome of 22 chromosomal loci shared across all three antibiotics, highlighting potential cross-resistance and the central roles of baeR, gadX, and marA in coordinating adaptive responses. Gene ontology enrichment underscored the positive regulation of gene expression and intracellular signaling as key themes in resistance evolution. Discussion. Our findings illustrate the multifaceted strategies E. coli employs—combining metabolic flexibility with sophisticated regulatory networks—to withstand diverse antibiotic pressures. This study underscores the utility of the MEGA-plate system in dissecting spatiotemporal AMR dynamics in a controlled yet ecologically relevant context. Conclusions. The divergent responses to meropenem and gentamicin highlight the complexity of resistance development and reinforce the need for integrated, One Health strategies. Targeting shared regulatory hubs may open new avenues for antimicrobial intervention and help preserve the efficacy of existing drugs.

Background/Objectives: In recent years, the discharge of antibiotics into rivers and irrigation canals has increased. However, few studies have addressed the impact of these compounds on agricultural fields that use such water to meet crop demands. Methods: In this study, the transport of two types of gentamicin (pure gentamicin and gentamicin sulfate) was modeled at concentrations of 150 and 300 μL/L, respectively, in a soil with more than 60 years of agricultural use. Infiltration tests under constant head conditions and gentamicin transport experiments were conducted in acrylic columns measuring 14 cm in length and 12.7 cm in diameter. The scaling parameters for the Richards equation were obtained from experimental data, while those for the advection–dispersion equation were estimated using inverse methods through a nonlinear optimization algorithm. In addition, a fractal-based model for saturated hydraulic conductivity was employed. Results: It was found that the dispersivity of gentamicin sulfate is 3.1 times higher than that of pure gentamicin. Based on the estimated parameters, two simulation scenarios were conducted: continuous application of gentamicin and soil flushing after antibiotic discharge. The results show that the transport velocity of gentamicin sulfate in the soil may have short-term consequences for the emergence of resistant microorganisms due to the destination of wastewater containing antibiotic residues. Conclusions: Finally, further research is needed to evaluate the impact of antibiotics on soil physical properties, as well as their effects on irrigated crops, animals that consume such water, and the soil microbiota.