Multiple Keys for a Single Lock: The Unusual Structural Plasticity of the Nucleotidyltransferase (4′)/Kanamycin Complex

The most common mode of bacterial resistance to aminoglycoside antibiotics is the enzyme‐catalysed chemical modification of the drug. Over the last two decades, significant efforts in medicinal chemistry have been focused on the design of non‐ inactivable antibiotics. Unfortunately, this strategy has met with limited success on account of the remarkably wide substrate specificity of aminoglycoside‐modifying enzymes. To understand the mechanisms behind substrate promiscuity, we have performed a comprehensive experimental and theoretical analysis of the molecular‐recognition processes that lead to antibiotic inactivation by Staphylococcus aureus nucleotidyltransferase 4′(ANT(4′)), a clinically relevant protein. According to our results, the ability of this enzyme to inactivate structurally diverse polycationic molecules relies on three specific features of the catalytic region. First, the dominant role of electrostatics in aminoglycoside recognition, in combination with the significant extension of the enzyme anionic regions, confers to the protein/antibiotic complex a highly dynamic character. The motion deduced for the bound antibiotic seem to be essential for the enzyme action and probably provide a mechanism to explore alternative drug inactivation modes. Second, the nucleotide recognition is exclusively mediated by the inorganic fragment. In fact, even inorganic triphosphate can be employed as a substrate. Third, ANT(4′) seems to be equipped with a duplicated basic catalyst that is able to promote drug inactivation through different reactive geometries. This particular combination of features explains the enzyme versatility and renders the design of non‐inactivable derivatives a challenging task.     

Determination of estrogens in environmental water samples using 1,3‐dipentylimidazolium hexafluorophosphate ionic liquid as extraction solvent in dispersive liquid–liquid microextraction

In this work, the potential of a symmetric dialkyl‐substituted ionic liquid (IL), 1,3‐dipenthylimidazolium hexafluorophosphate ([PPIm][PF₆]), as extraction solvent in dispersive liquid–liquid microextraction (DLLME) has been studied for the analysis of a group of three natural (estriol, 17β‐estradiol, and 17α‐estradiol) and four synthetic (17α‐ethynylestradiol, diethylstibestrol, dienestrol, and hexestrol) estrogenic compounds as well as one mycotoxin with estrogenic activity (zearalenone) in different types of water samples (Milli‐Q, mineral, and wastewater). Separation, determination, and quantification were developed by HPLC‐DAD and a fluorescence detector (FD) connected in series. Factors influencing the IL‐DLLME procedure (sample pH, amount of IL, type and volume of disperser solvent, ionic strength, and assistance of vortex agitation) were investigated and optimized by means of a step‐by‐step approach. Once the optimum extraction conditions were established (10 mL of water at pH 8, 60 mg of [PPIm][PF₆], 500 μL of ACN as disperser solvent and vortex agitation for 1 min), the calibration curves of the whole method (IL‐DLLME‐HPLC‐DAD/FD) were obtained and precision and accuracy were evaluated. It was demonstrated that the developed methodology was repeatable, accurate, and selective with limits of detection in the 0.30–0.57 μg/L and 13.8–37.1 μg/L range for FD and DAD, respectively. Relative recovery values were higher than 85% for the different types of water samples and the Student's t test demonstrated that there were not significant differences between the added and the found concentration.     

Dual Amperometric Immunosensor for Improving Cancer Metastasis Detection by the Simultaneous Determination of Extracellular and Soluble Circulating Fraction of Emerging Metastatic Biomarkers

This paper reports the development of a dual immunosensor using magnetic microcarriers (MBs) and amperometric transduction at dual screen‐printed carbon electrodes (SPdCEs) for the simultaneous determination of two biomarkers: interleukin‐13 receptor α2 (IL‐13Rα2) and E‐cadherin (E‐CDH), with both extracellular and soluble fraction; oncogenic and tumor suppressor markers, respectively, of great relevance in metastatic processes. The implemented methodology involved the formation of sandwich‐type immunocomplexes using specific capture antibodies immobilized onto carboxylic acid magnetic microbeads (HOOC‐MBs), and biotinylated detector antibodies labeled with streptavidin?horseradish peroxidase conjugates (Strep‐HRP). The amperometric detection was performed by addition of hydrogen peroxide in the presence of hydroquinone (HQ) as the redox mediator. The dual immunosensing platform provided linear calibration ranges suitable for the determination of both biomarkers in liquid and solid clinical specimens as well as excellent selectivity against other cancer biomarkers. This simple handling dual bioplatform was applied to the determination of the soluble and extracellular fraction of the target biomarkers in serum and paraffined‐embedded tissues from colorectal cancer (CRC) patients diagnosed at different tumor grade. The obtained results reveal great potential of this configuration to improve the reliability in diagnosing metastatic CRC.     

Engineering Iron–Nickel Nanoparticles for Magnetically Induced CO2 Methanation in Continuous Flow

Induction heating of magnetic nanoparticles (NPs) is a method to activate heterogeneous catalytic reactions. It requires nano‐objects displaying high heating power and excellent catalytic activity. Here, using a surface engineering approach, bimetallic NPs are used for magnetically induced CO₂ methanation, acting both as heating agent and catalyst. The organometallic synthesis of Fe₃₀Ni₇₀ NPs displaying high heating powers at low magnetic field amplitudes is described. The NPs are active but only slightly selective for CH₄ after deposition on SiRAlOx owing to an iron‐rich shell (25 mL min^?1, 25 mT, 300 kHz, conversion 71 %, methane selectivity 65 %). Proper surface engineering consisting of depositing a thin Ni layer leads to Fe₃₀Ni₇₀@Ni NPs displaying a very high activity for CO₂ hydrogenation and a full selectivity. A quantitative yield in methane is obtained at low magnetic field and mild conditions (25 mL min^?1, 19 mT, 300 kHz, conversion 100 %, methane selectivity 100 %).     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.     

Conformational selection of glycomimetics at enzyme catalytic sites: experimental demonstration of the binding of distinct high-energy distorted conformations of C-, S-, and O-glycosides by E. Coli beta-galactosidases

We show that the conformational features of the molecular complexes of E. coli beta-galactosidase and O-glycosides may differ from those formed with closely related compounds in their chemical nature, such as C- and S-glycosyl analogues. In the particular case presented here, NMR and ab initio quantum mechanical results show that the 3D-shapes of the ligand/inhibitor within the enzyme binding site depend on the chemical nature of the compounds. In fact, they depend on the relative size of the stereoelectronic barriers for chair deformation or for rotation around Phi glycosidic linkage.     

Conformational differences between O- and C-glycosides: the alpha-O-man-(1-->1)-beta-Gal/alpha-C-Man-(1-->1)-beta-Gal case--a decisive demonstration of the importance of the exo-anomeric effect on the conformation of glycosides

The conformational behavior of alpha-O-Man-(1-->1)-beta-Gal (1) and its C-analogue (2) has been studied using J/NOE NMR data, molecular mechanics, molecular dynamics, and ab initio calculations. The population distribution around the glycosidic linkages of 1 and 2 is rather different, especially for the alpha-Man linkage. A lower limit for the exo-anomeric effect in water has been experimentally determined.