Changes in the Release of Endothelial Extracellular Vesicles CD144+, CCR6+, and CXCR3+ in Individuals with Acute Myocardial Infarction.

Acute myocardial infarction (AMI) results from vulnerable plaque rupture, causing ischemic cardiomyocyte necrosis and intense inflammation. Paradoxically, this inflammation releases factors that aid heart repair. Recent findings suggest a role for extracellular vesicles (EVs) in intercellular communication during post-AMI cardiac repair. However, EVs' tissue origin and chemokine profile in the blood of patients with AMI remains unclear. This study characterized the tissue origin and chemokine receptor profile of EVs in the coronary and peripheral blood of patients with AMI. The results reveal that vesicles isolated from coronary and peripheral blood plasma are enriched in tetraspanin (CD9) and express CD81+, CD90+, and CD144+. The vesicle size ranged between 145 and 162 nm, with the control group exhibiting smaller vesicles (D10) than the AMI group. Furthermore, all vesicles expressed CCR6 and CXCR3, whereas a small percentage expressed CCR4. In addition, a decrease in CXCR3 and CCR6 expression was observed in coronary and peripheral AMI blood vesicles compared with the control; however, no difference was found between AMI coronary and AMI peripheral blood vesicles. In conclusion, our study demonstrates, for the first time, changes in the number of extracellular vesicles expressing CD144+, CXCR3, and CCR6 in the peripheral circulation of patients with AMI. Extracellular vesicles present in the circulation of patients with AMI hold excellent promise as a potential diagnostic tool.

Small-Molecule:Polymer Composites for Transparent Films with Visible Emission.

The analysis of the shift in photoluminescence emission for a blend of polyvinylcarbazole and acrylonitrile derivative compounds is reported. The small-molecule compounds have different functional groups, phenyl, pyridine, or methyl phenyl, attached to an acrylonitrile group. According to the functional group, the blue emission for pure dye shifts to green or yellowish in the blend film. Several PVK:dye ratios from 0:100 to 20:80 were used for film deposition. The film morphology was analyzed by atomic force microscopy; for low dye content, homogeneous films were achieved. However, aggregates of several micrometers are formed on the surface of films with higher dye concentrations. The shift in emission occurs only with PVK, and for a non-conjugated matrix such as polystyrene, the emission remains unchanged. The interaction of dyes with PVK leading to change in emission was also achieved by grinding dye and polymer. Results showed that shifts in emission could come from exciplex formation along with changes in dye intermolecular interactions. The blend films were highly transparent in the visible spectra due to the absorption in the UV region for dye and matrix. The films with ratio PVK: dye ratio 80:20 was used as active layer in OLEDs.

Successful pharmaco-invasive approach using a lower alteplase dose and VA-ECMO support in high-risk pulmonary embolism: case report.

Despite the elevated mortality rates associated with high-risk pulmonary embolism (PE), this condition remains understudied. Data regarding the effectiveness and safety of invasive therapies such as venoarterial extracorporeal membrane oxygenation (VA-ECMO) in this patient population remains controversial. Here, we present the case of a 61-year-old male with high-risk PE associated with refractory cardiac arrest and cardiogenic shock who underwent a combination of extracorporeal cardiopulmonary resuscitation with VA-ECMO and pharmaco-invasive therapy (mechanical thrombi fragmentation plus lower alteplase dose), resulting in successful pulmonary reperfusion. After a prolonged in-hospital stay, the patient was discharged in stable condition.

Simple and Fast Prediction of Gestational Diabetes Mellitus Based on Machine Learning and Near-Infrared Spectra of Serum: A Proof of Concept Study at Different Stages of Pregnancy.

Gestational diabetes mellitus (GDM) is a hyperglycemic state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, has low reproducibility, and results are tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to produce a result. Near-infrared (NIR) spectroscopy is a simple, fast, and low-cost analytical technique that has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and duration of analysis. Serum samples from the first trimester (before GDM diagnosis) and the second trimester (at the time of GDM diagnosis) of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 mathematical pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best models for first and second trimester achieved areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR-spectroscopy-based methods for the prediction of GDM. The developed methods allow for prediction of GDM from 10 µL of serum in only 32 min. They are simple, fast, and have a great potential for application in clinical practice, especially as alternative screening tools to the OGTT for GDM diagnosis.

Clinical and pulmonary function analysis in long-COVID revealed that long-term pulmonary dysfunction is associated with vascular inflammation pathways and metabolic syndrome.

Introduction: Long-term pulmonary dysfunction (L-TPD) is one of the most critical manifestations of long-COVID. This lung affection has been associated with disease severity during the acute phase and the presence of previous comorbidities, however, the clinical manifestations, the concomitant consequences and the molecular pathways supporting this clinical condition remain unknown. The aim of this study was to identify and characterize L-TPD in patients with long-COVID and elucidate the main pathways and long-term consequences attributed to this condition by analyzing clinical parameters and functional tests supported by machine learning and serum proteome profiling. Methods: Patients with L-TPD were classified according to the results of their computer-tomography (CT) scan and diffusing capacity of the lungs for carbon monoxide adjusted for hemoglobin (DLCOc) tests at 4 and 12-months post-infection. Results: Regarding the acute phase, our data showed that L-TPD was favored in elderly patients with hypertension or insulin resistance, supported by pathways associated with vascular inflammation and chemotaxis of phagocytes, according to computer proteomics. Then, at 4-months post-infection, clinical and functional tests revealed that L-TPD patients exhibited a restrictive lung condition, impaired aerobic capacity and reduced muscular strength. At this time point, high circulating levels of platelets and CXCL9, and an inhibited FCgamma-receptor-mediated-phagocytosis due to reduced FcγRIII (CD16) expression in CD14+ monocytes was observed in patients with L-TPD. Finally, 1-year post infection, patients with L-TPD worsened metabolic syndrome and augmented body mass index in comparison with other patient groups. Discussion: Overall, our data demonstrated that CT scan and DLCOc identified patients with L-TPD after COVID-19. This condition was associated with vascular inflammation and impair phagocytosis of virus-antibody immune complexes by reduced FcγRIII expression. In addition, we conclude that COVID-19 survivors required a personalized follow-up and adequate intervention to reduce long-term sequelae and the appearance of further metabolic diseases.

Weak noncovalent interactions in two positional isomers of acrylonitrile derivatives: inputs from PIXEL energy, Hirshfeld surface and QTAIM analyses.

A single crystal X-ray diffraction analysis was performed on two positional isomers (m-tolyl and p-tolyl) of acrylonitrile derivatives, namely, (Z)-3-(4-(pyridin-2-yl) phenyl)-2-(m-tolyl) acrylonitrile (1) and (Z)-3-(4-(pyridin-2-yl)phenyl)-2-(p-tolyl) acrylonitrile (2). Compound 1 crystallized in the monoclinic P21/n space group with two crystallographically independent molecules. Compound 2 also possesses two crystallographically independent molecules and crystallized in the triclinic P-1 space group. The Hirshfeld surface analysis revealed that, in both isomers, intermolecular H⋅⋅⋅H/C/N contacts contribute significantly to the crystal packing. More than 40% of the contribution arises from intermolecular C-H⋅⋅⋅C(π) contacts. In both compounds, the relative contribution of these contacts is comparable, indicating that the positional isomeric effects are marginal. The structures in which these isomers are arranged in the solid state are very similar, and the lattice energies are also comparable between the isomers. The Coulomb-London-Pauli-PIXEL (CLP-PIXEL) energy analysis identified the energetically significant dimers. The strength of the intra- and intermolecular interactions was evaluated using the quantum theory of atoms in molecules approach. The UV-Vis absorbance in three different solvents (chloroform, ethanol, and ethyl acetate) for isomers 1 and 2 are very similar. This result is in good agreement with the time-dependent density-functional theory (TD-DFT) calculations.

Machine learning applied in maternal and fetal health: a narrative review focused on pregnancy diseases and complications.

Introduction: Machine learning (ML) corresponds to a wide variety of methods that use mathematics, statistics and computational science to learn from multiple variables simultaneously. By means of pattern recognition, ML methods are able to find hidden correlations and accomplish accurate predictions regarding different conditions. ML has been successfully used to solve varied problems in different areas of science, such as psychology, economics, biology and chemistry. Therefore, we wondered how far it has penetrated into the field of obstetrics and gynecology. Aim: To describe the state of art regarding the use of ML in the context of pregnancy diseases and complications. Methodology: Publications were searched in PubMed, Web of Science and Google Scholar. Seven subjects of interest were considered: gestational diabetes mellitus, preeclampsia, perinatal death, spontaneous abortion, preterm birth, cesarean section, and fetal malformations. Current state: ML has been widely applied in all the included subjects. Its uses are varied, the most common being the prediction of perinatal disorders. Other ML applications include (but are not restricted to) biomarker discovery, risk estimation, correlation assessment, pharmacological treatment prediction, drug screening, data acquisition and data extraction. Most of the reviewed articles were published in the last five years. The most employed ML methods in the field are non-linear. Except for logistic regression, linear methods are rarely used. Future challenges: To improve data recording, storage and update in medical and research settings from different realities. To develop more accurate and understandable ML models using data from cutting-edge instruments. To carry out validation and impact analysis studies of currently existing high-accuracy ML models. Conclusion: The use of ML in pregnancy diseases and complications is quite recent, and has increased over the last few years. The applications are varied and point not only to the diagnosis, but also to the management, treatment, and pathophysiological understanding of perinatal alterations. Facing the challenges that come with working with different types of data, the handling of increasingly large amounts of information, the development of emerging technologies, and the need of translational studies, it is expected that the use of ML continue growing in the field of obstetrics and gynecology.

No association of the dopamine D2 receptor genetic bilocus score (rs1800497/rs1799732) on food addiction and food reinforcement in Chilean adults.

Purpose: Different systems regulate food intake. In the reward system, dopamine (DA) is the main neurotransmitter, and a variety of genetic variants (rs1799732 and rs1800497) are associated with addiction. Addiction is a highly polygenic disease, where each allelic variant adds a small amount of vulnerability. Polymorphisms rs1799732 and rs1800497 are associated with eating behavior and hedonic hunger, but links to food addiction remain unclear. Aim: To evaluate the association between the bilocus profile (rs1799732-rs1800497) of the dopaminergic pathway with food reinforcement and food addiction in Chilean adults. Methods: A cross-sectional study recruited a convenience sample of 97 obese, 25 overweight, and 99 normal-weight adults (18-35 years). Anthropometric measurements were performed by standard procedures and eating behavior was assessed using the: Food Reinforcement Value Questionnaire (FRVQ) and Yale Food Addiction scale (YFAS). The DRD2 genotypes were determined by TaqMan assays (rs1800497 and rs1799732). A bilocus composite score was calculated. Results: In the normal weight group, individuals who were heterozygous for the rs1977932 variant (G/del) showed higher body weight (p-value 0.01) and abdominal circumference (p-value 0.01) compared to those who were homozygous (G/G). When analyzing rs1800497, a significant difference in BMI was observed for the normal weight group (p-value 0.02) where heterozygous showed higher BMI. In the obese group, homozygous A1/A1 showed higher BMI in comparison to A1/A2 and A2/A2 (p-value 0.03). Also, a significant difference in food reinforcement was observed in the rs1800497, where homozygous for the variant (A1A1) show less reinforcement (p-value 0.01).In relation to the bilocus score in the total sample, 11% showed "very low dopaminergic signaling", 24.4% were "under", 49.7% showed "intermediate signaling", 12.7% showed "high" and 1.4% showed "very high". No significant genotypic differences were observed in food reinforcement and food addiction by bilocus score. Conclusions: The results indicate that the genetic variants rs1799732 and rs1800497 (Taq1A) were associated with anthropometric measurements but not with food addiction or food reinforcement in Chilean university students. These results suggest that other genotypes, such as rs4680 and rs6277, which affect DA signaling capacity through a multilocus composite score, should be studied. Level V: Evidence obtained from a cross-sectional descriptive study.

Adenosine promoted angiogenesis mediated by the release of small extracellular vesicles from human endothelial progenitor cells.

Endothelial progenitor cells (EPCs) are stem cells mainly derived from bone marrow; from where they migrate to repair and regenerate damaged tissues. eEPCs have been classified into two sub-populations, early (eEPC) and late EPCs (lEPC), depending on maturation stages in vitro. In addition, eEPC release endocrine mediators, including small extracellular vesicles (sEVs), which in turn may enhance the eEPC-mediated wound healing properties. Nevertheless, adenosine contributes to angiogenesis by recruiting eEPC at the injury site. However, whether ARs may enhance the secretome of eEPC, including sEVs, is unknown. Therefore, we aimed to investigate whether AR activation increase the release of sEVs in eEPC, which in turn has paracrine effects on recipient endothelial cells. Results shown that 5'-N-ethylcarboxamidoadenosine (NECA), a non-selective agonist, increase both the protein levels of the vascular endothelial growth factor (VEGF), and the number of sEVs released to the conditioned medium (CM) in primary culture of eEPC. Importantly, CM and EVs harvested from NECA-stimulated eEPC promote in vitro angiogenesis, without changes in cell proliferation, in recipient ECV-304 endothelial cells. This constitutes the first evidence showing that adenosine enhances sEVs release from eEPC, which has pro-angiogenic capacity on recipient endothelial cells.

Evaluation of first and second trimester maternal thyroid profile on the prediction of gestational diabetes mellitus and post load glycemia.

Maternal thyroid alterations have been widely associated with the risk of gestational diabetes mellitus (GDM). This study aims to 1) test the first and the second trimester full maternal thyroid profile on the prediction of GDM, both alone and combined with non-thyroid data; and 2) make that prediction independent of the diagnostic criteria, by evaluating the effectiveness of the different maternal variables on the prediction of oral glucose tolerance test (OGTT) post load glycemia. Pregnant women were recruited in Concepción, Chile. GDM diagnosis was performed at 24-28 weeks of pregnancy by an OGTT (n = 54 for normal glucose tolerance, n = 12 for GDM). 75 maternal thyroid and non-thyroid parameters were recorded in the first and the second trimester of pregnancy. Various combinations of variables were assessed for GDM and post load glycemia prediction through different classification and regression machine learning techniques. The best predictive models were simplified by variable selection. Every model was subjected to leave-one-out cross-validation. Our results indicate that thyroid markers are useful for the prediction of GDM and post load glycemia, especially at the second trimester of pregnancy. Thus, they could be used as an alternative screening tool for GDM, independently of the diagnostic criteria used. The final classification models predict GDM with cross-validation areas under the receiver operating characteristic curve of 0.867 (p<0.001) and 0.920 (p<0.001) in the first and the second trimester of pregnancy, respectively. The final regression models predict post load glycemia with cross-validation Spearman r correlation coefficients of 0.259 (p = 0.036) and 0.457 (p<0.001) in the first and the second trimester of pregnancy, respectively. This investigation constitutes the first attempt to test the performance of the whole maternal thyroid profile on GDM and OGTT post load glycemia prediction. Future external validation studies are needed to confirm these findings in larger cohorts and different populations.

Tipos de partos y niveles de oxitocina, cortisol y hormonas tiroideas en plasma del cordón umbilical / Types of deliveries and levels of oxytocin, cortisol and thyroid hormones in umbilical cord plasma

Introducción: La placenta sintetiza y secreta varias hormonas que permiten la regulación del embarazo, el trabajo de parto y la adaptación metabólica materno-fetal. Su comportamiento asociado al tipo de parto puede dar información relevante sobre efectos epigenéticos. Objetivo: Describir el tipo de parto con los niveles de oxitocina, cortisol y hormonas tiroideas en plasma de cordón umbilical al nacer. Método: A 50 mujeres con embarazos principalmente normales se les cuantificaron los niveles neurohormonales en plasma de cordón umbilical, obtenido inmediatamente tras el periodo expulsivo. Los resultados se incorporaron a la base de datos clínicos de cada participante y se analizaron con Stata v.14.0. El protocolo fue aprobado por el comité de ética. Resultados: Hubo 33 partos vaginales (12 espontáneos, 13 acelerados y 8 inducidos) y 17 cesáreas (7 electivas y 10 de urgencia). Se observaron mayores niveles de cortisol en los partos vaginales acelerados; las cesáreas tuvieron menores niveles de cortisol y hormona estimulante de la tiroides. Las intervenciones clínicas, con altos o bajos niveles hormonales, están en directa relación con el tipo de parto. Conclusiones: El cortisol y la hormona estimulante de la tiroides medidos en plasma de cordón umbilical variaron según el tipo de parto. Esto es una primera cuantificación de hormonas en plasma de cordón umbilical y su posible regulación placentaria a propósito del tipo de parto.

Introduction: The placenta synthesizes and secretes several hormones allowing the regulation of pregnancy, labor and maternal-fetal metabolic adaptation. Their behavior associated with the type of delivery, may provide relevant information on epigenetic effects. Objective: To describe the type of delivery with the levels of oxytocin, cortisol and thyroid hormones in umbilical cord plasma at birth. Method: Neurohormonal levels from umbilical cord plasma obtained immediately post expulsion, were quantified in 50 women with mainly normal pregnancies. Results incorporated into the clinical database of each participant, statistically analyzed in Stata v.14.0. Protocol approved by ethics committee. Results: 33 were vaginal deliveries (12 spontaneous, 13 accelerated, 8 induced) and 17 cesarean sections (7 elective and 10 emergency). Higher cortisol levels were observed in accelerated vaginal deliveries, cesarean sections had lower cortisol and thyroid stimulating hormone levels. While clinical interventions, with high or low hormone levels, were related to the type of delivery. Conclusions: Cortisol and thyroid stimulating hormone measured in umbilical cord plasma varied according to the type of delivery. This is a first quantification of hormones in umbilical cord plasma and their possible placental regulation in relation to the type of delivery.

Machine learning-based models for gestational diabetes mellitus prediction before 24-28 weeks of pregnancy: A review.

Gestational Diabetes Mellitus (GDM) is a hyperglycemia state that impairs maternal and offspring health, short and long-term. It is usually diagnosed at 24-28 weeks of pregnancy (WP), but at that time the fetal phenotype is already altered. Machine learning (ML)-based models have emerged as an auspicious alternative to predict this pathology earlier, however, they must be validated in different populations before their implementation in routine clinical practice. This review aims to give an overview of the ML-based models that have been proposed to predict GDM before 24-28 WP, with special emphasis on their current validation state and predictive performance. Articles were searched in PubMed. Manuscripts written in English and published before January 1, 2022, were considered. 109 original research studies were selected, and categorized according to the type of variables that their models involved: medical, i.e. clinical and/or biochemical parameters; alternative, i.e. metabolites, peptides or proteins, micro-ribonucleic acid molecules, microbiota genera, or other variables that did not fit into the first category; or mixed, i.e. both medical and alternative data. Only 8.3 % of the reviewed models have had validation in independent studies, with low or moderate performance for GDM prediction. In contrast, several models that lack of independent validation have shown a very high predictive power. The evaluation of these promising models in future independent validation studies would allow to assess their performance on different populations, and continue their way towards clinical implementation. Once settled, ML-based models would help to predict GDM earlier, initiate its treatment timely and prevent its negative consequences on maternal and offspring health.

Loxin Reduced the Inflammatory Response in the Liver and the Aortic Fatty Streak Formation in Mice Fed with a High-Fat Diet.

Oxidized low-density lipoprotein (ox-LDL) is the most harmful form of cholesterol associated with vascular atherosclerosis and hepatic injury, mainly due to inflammatory cell infiltration and subsequent severe tissue injury. Lox-1 is the central ox-LDL receptor expressed in endothelial and immune cells, its activation regulating inflammatory cytokines and chemotactic factor secretion. Recently, a Lox-1 truncated protein isoform lacking the ox-LDL binding domain named LOXIN has been described. We have previously shown that LOXIN overexpression blocked Lox-1-mediated ox-LDL internalization in human endothelial progenitor cells in vitro. However, the functional role of LOXIN in targeting inflammation or tissue injury in vivo remains unknown. In this study, we investigate whether LOXIN modulated the expression of Lox-1 and reduced the inflammatory response in a high-fat-diet mice model. Results indicate that human LOXIN blocks Lox-1 mediated uptake of ox-LDL in H4-II-E-C3 cells. Furthermore, in vivo experiments showed that overexpression of LOXIN reduced both fatty streak lesions in the aorta and inflammation and fibrosis in the liver. These findings were associated with the down-regulation of Lox-1 in endothelial cells. Then, LOXIN prevents hepatic and aortic tissue damage in vivo associated with reduced Lox-1 expression in endothelial cells. We encourage future research to understand better the underlying molecular mechanisms and potential therapeutic use of LOXIN.

Solution and Solid-State Photophysical Properties of Positional Isomeric Acrylonitrile Derivatives with Core Pyridine and Phenyl Moieties: Experimental and DFT Studies.

The compounds I (Z)-2-(phenyl)-3-(2,4,5-trimethoxyphenyl)acrylonitrile with one side (2,4,5-MeO-), one symmetrical (2Z,2'Z)-2,2'-(1,4-phenylene)bis(3-(2,4,5-trimethoxyphenyl)acrylonitrile), II (both sides with (2,4,5-MeO-), and three positional isomers with pyridine (Z)-2-(pyridin-2- 3, or 4-yl)-3-(2,4,5-trimethoxyphenyl)acrylonitrile, III-V were synthetized and characterized by UV-Vis, fluorescence, IR, H1-NMR, and EI mass spectrometry as well as single crystal X-ray diffraction (SCXRD). The optical properties were strongly influenced by the solvent (hyperchromic and hypochromic shift), which were compared with the solid state. According to the solvatochromism theory, the excited-state (µe) and ground-state (µg) dipole moments were calculated based on the variation of Stokes shift with the solvent's relative permittivity, refractive index, and polarity parameters. SCXRD analyses revealed that the compounds I and II crystallized in the monoclinic system with the space group, P21/n and P21/c, respectively, and with Z = 4 and 2. III, IV, and V crystallized in space groups: orthorhombic, Pbca; triclinic, P-1; and monoclinic, P21 with Z = 1, 2, and 2, respectively. The intermolecular interactions for compounds I-V were investigated using the CCDC Mercury software and their energies were quantified using PIXEL. The density of states (DOS), molecular electrostatic potential surfaces (MEPS), and natural bond orbitals (NBO) of the compounds were determined to evaluate the photophysical properties.

In-vivo measurement of the fluorescence spectrum of wild cochineal (Dactylopius opuntiae).

It is known that the harmful presence of the wild cochineal (Dactylopius opuntiae), unlike the fine cochineal (Dactylopius coccus), in prickly pear crops of farmers leads to consider it as one of the major pests for this crop. In this study, we present the implementation of an optical setup that ensures the measurement of the in-vivo fluorescence spectra of wild cochineals ranging in size from 440 to 1190 µm in their natural habitat achieved by developing a reproduction model adopted from available literature. It was observed that in-vivo fluorescence spectra of these insects were comprised in the spectral region of 570-760 nm, showing a proportional dependence between the fluorescence intensity emitted and the cochineal size. In addition, we have considered other spectral parameters to perform the comparison between fluorescence spectra of the different cochineal sizes. These results provide the basis for the development of novel methodologies and equipment aimed towards the early detection of this pest in prickly pear crops from its early growth stages (nymph I and II).

Maternal thyroid profile in first and second trimester of pregnancy is correlated with gestational diabetes mellitus through machine learning.

There is evidence about a possible relationship between thyroid abnormalities and gestational diabetes mellitus (GDM). However, there is still no conclusive data on this dependence, since no strong correlation has been proved. In this work, we used machine learning to determine whether there is a correlation between maternal thyroid profile in first and second trimester of pregnancy and GDM. Using principal component analysis, it was possible to find an evident correlation between both, which could be used as a complement for a more sensitive GDM diagnosis.

High levels of maternal total tri-iodothyronine, and low levels of fetal free L-thyroxine and total tri-iodothyronine, are associated with altered deiodinase expression and activity in placenta with gestational diabetes mellitus.

Gestational Diabetes Mellitus (GDM) is characterized by abnormal maternal D-glucose metabolism and altered insulin signaling. Dysregulation of thyroid hormones (TH) tri-iodethyronine (T3) and L-thyroxine (T4) Hormones had been associated with GDM, but the physiopathological meaning of these alterations is still unclear. Maternal TH cross the placenta through TH Transporters and their Deiodinases metabolize them to regulate fetal TH levels. Currently, the metabolism of TH in placentas with GDM is unknown, and there are no other studies that evaluate the fetal TH from pregnancies with GDM. Therefore, we evaluated the levels of maternal TH during pregnancy, and fetal TH at delivery, and the expression and activity of placental deiodinases from GDM pregnancies. Pregnant women were followed through pregnancy until delivery. We collected blood samples during 10-14, 24-28, and 36-40 weeks of gestation for measure Thyroid-stimulating hormone (TSH), Free T4 (FT4), Total T4 (TT4), and Total T3 (TT3) concentrations from Normal Glucose Tolerance (NGT) and GDM mothers. Moreover, we measure fetal TSH, FT4, TT4, and TT3 in total blood cord at the delivery. Also, we measured the placental expression of Deiodinases by RT-PCR, western-blotting, and immunohistochemistry. The activity of Deiodinases was estimated quantified rT3 and T3 using T4 as a substrate. Mothers with GDM showed higher levels of TT3 during all pregnancy, and an increased in TSH during second and third trimester, while lower concentrations of neonatal TT4, FT4, and TT3; and an increased TSH level in umbilical cord blood from GDM. Placentae from GDM mothers have a higher expression and activity of Deiodinase 3, but lower Deiodinase 2, than NGT mothers. In conclusion, GDM favors high levels of TT3 during all gestation in the mother, low levels in TT4, FT4 and TT3 at the delivery in neonates, and increases deiodinase 3, but reduce deiodinase 2 expression and activity in the placenta.

[National surveillance of clinical isolates of Enterococcus faecalis resistant to linezolid carrying the optrA gene in Colombia, 2014-2019]. / Vigilancia nacional de aislamientos clínicos de Enterococcus faecalis resistentes al linezolid portadores del gen optrA en Colombia, 2014-2019.

OBJECTIVE: To describe the epidemiological, phenotypical and genetic characteristics of clinical isolates carrying the optrA gene identified in antimicrobial resistance surveillance by the laboratory of the National Institute of Health of Colombia. METHODS: Between October 2014 and February 2019, 25 isolates of Enterococcus spp. resistant to linezolid were received. Antimicrobial identification and sensitivity were determined using Vitek 2 and the minimum inhibitory concentration (MIC) to linezolid was established with E-test. The optrA gene was detected by PCR, and the genetic diversity of optrA-positive isolates was tested with Diversilab®. Six isolates were selected to perform whole genome sequencing. RESULTS: The optrA gene was confirmed in 23/25 isolates of E. faecalis from seven departments in Colombia. The isolates presented a MIC to linezolid between 8 and >256µg/mL. Typing by Diversilab® showed a wide genetic variability. All the isolates analyzed by whole genome sequencing showed the resistance genes fexA, ermB, lsaA, tet(M), tet(L) and dfrG in addition to optrA and were negative for other mechanisms of resistance to linezolid. Three type sequences and three optrA variants were identified: ST16 (optrA-2), ST476 (optrA-5) and ST618 (optrA-6). The genetic environment of the optrA-2 (ST16) isolates presented the impB, fex, optrA segment, associated with plasmid, while in two isolates (optrA-6 and optrA-5) the transferable chromosomal element Tn6674-like was found. CONCLUSION: OptrA-positive clinical isolates present a high genetic diversity, with different optrA clones and variants related to two types of structures and different mobile genetic elements.

Vigilancia nacional de aislamientos clínicos de Enterococcus faecalis resistentes al linezolid portadores del gen optrA en Colombia, 2014-2019

Objetivo. Describir las características epidemiológicas, fenotípicas y genéticas de aislamientos clínicos portadores de optrA identificados en la vigilancia de resistencia antimicrobiana por el laboratorio del Instituto Nacional de Salud de Colombia. Métodos. Entre octubre de 2014 y febrero 2019, se recibieron 25 aislamientos de Enterococcus spp. resistentes al linezolid. La identificación y sensibilidad antimicrobiana se determinó con Vitek 2 y la concentración inhibitoria mínima (CIM) al linezolid se estableció con E-test. El gen optrA se detectó mediante PCR. La diversidad genética de aislamientos positivos para optrA se analizó con Diversilab®. Se seleccionaron seis aislamientos para llevar a cabo la secuenciación del genoma completo. Resultados. Se confirmó el gen optrA en 23/25 aislamientos de E. faecalis de siete departamentos de Colombia. Los aislamientos presentaron una CIM al linezolid entre 8 y >256μg/mL. La tipificación por Diversilab® indicó una amplia variabilidad genética. Todos los aislamientos analizados mediante secuenciación del genoma completo, presentaron genes de resistencia fexA, ermB, lsaA, tet(M), tet(L) y dfrG además de optrA y fueron negativos para otros mecanismos de resistencia al linezolid. Se identificaron tres secuencias tipos y tres variantes de optrA: ST16 (optrA-2), ST476 (optrA-5) y ST618 (optrA-6). El entorno genético de los aislamientos optrA-2 (ST16) presentó el segmento impB, fex, optrA, asociado a plásmido, mientras que en dos aislamientos (optrA-6 y optrA-5) se encontró el elemento cromosómico transferible Tn6674-like. Conclusión. Los aislamientos clínicos positivos para optrA presentan una alta diversidad genética, con diferentes clones y variantes de optrA relacionados con dos tipos de estructuras y diferentes elementos genéticos móviles.

Objective. To describe the epidemiological, phenotypical and genetic characteristics of clinical isolates carrying the optrA gene identified in antimicrobial resistance surveillance by the laboratory of the National Institute of Health of Colombia. Methods. Between October 2014 and February 2019, 25 isolates of Enterococcus spp. resistant to linezolid were received. Antimicrobial identification and sensitivity were determined using Vitek 2 and the minimum inhibitory concentration (MIC) to linezolid was established with E-test. The optrA gene was detected by PCR, and the genetic diversity of optrA-positive isolates was tested with Diversilab®. Six isolates were selected to perform whole genome sequencing. Results. The optrA gene was confirmed in 23/25 isolates of E. faecalis from seven departments in Colombia. The isolates presented a MIC to linezolid between 8 and >256μg/mL. Typing by Diversilab® showed a wide genetic variability. All the isolates analyzed by whole genome sequencing showed the resistance genes fexA, ermB, lsaA, tet(M), tet(L) and dfrG in addition to optrA and were negative for other mechanisms of resistance to linezolid. Three type sequences and three optrA variants were identified: ST16 (optrA-2), ST476 (optrA-5) and ST618 (optrA-6). The genetic environment of the optrA-2 (ST16) isolates presented the impB, fex, optrA segment, associated with plasmid, while in two isolates (optrA-6 and optrA-5) the transferable chromosomal element Tn6674-like was found. Conclusion. OptrA-positive clinical isolates present a high genetic diversity, with different optrA clones and variants related to two types of structures and different mobile genetic elements.

The activity of IKCa and BKCa channels contributes to insulin-mediated NO synthesis and vascular tone regulation in human umbilical vein.

Insulin regulates the l-arginine/nitric oxide (NO) pathway in human umbilical vein endothelial cells (HUVECs), increasing the plasma membrane expression of the l-arginine transporter hCAT-1 and inducing vasodilation in umbilical and placental veins. Placental vascular relaxation induced by insulin is dependent of large conductance calcium-activated potassium channels (BKCa), but the role of KCa channels on l-arginine transport and NO synthesis is still unknown. The aim of this study was to determine the contribution of KCa channels in both insulin-induced l-arginine transport and NO synthesis, and its relationship with placental vascular relaxation. HUVECs, human placental vein endothelial cells (HPVECs) and placental veins were freshly isolated from umbilical cords and placenta from normal pregnancies. Cells or tissue were incubated in absence or presence of insulin and/or tetraethylammonium, 1-[(2-chlorophenyl)diphenylmethyl]-1H-pyrazole, iberiotoxin or NG-nitro-l-arginine methyl ester. l-Arginine uptake, plasma membrane polarity, NO levels, hCAT-1 expression and placenta vascular reactivity were analyzed. The inhibition of intermediate-conductance KCa (IKCa) and BKCa increases l-arginine uptake, which was related with protein abundance of hCAT-1 in HUVECs. IKCa and BKCa activities contribute to NO-synthesis induced by insulin but are not directly involved in insulin-stimulated l-arginine uptake. Long term incubation (8 h) with insulin increases the plasma membrane hyperpolarization and hCAT-1 expression in HUVECs and HPVECs. Insulin-induced relaxation in placental vasculature was reversed by KCa inhibition. The results show that the activity of IKCa and BKCa channels are relevant for both physiological regulations of NO synthesis and vascular tone regulation in the human placenta, acting as a part of negative feedback mechanism for autoregulation of l-arginine transport in HUVECs.