Sex and disease severity-based analysis of steroid hormones in ME/CFS.

PURPOSE: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease characterized by persistent fatigue and decreased daily activity following physical and/or cognitive exertion. While ME/CFS affects both sexes, there is a higher prevalence in women. However, studies evaluating this sex-related bias are limited. METHODS: Circulating steroid hormones, including mineralocorticoids (aldosterone), glucocorticoids (cortisol, corticosterone, 11-deoxycortisol, cortisone), androgens (androstenedione, testosterone), and progestins (progesterone, 17α-hydroxyprogesterone), were measured in plasma samples using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Samples were obtained from mild/moderate (ME/CFSmm; females, n=20; males, n=8), severely affected patients (ME/CFSsa; females, n=24; males, n=6), and healthy controls (HC, females, n=12; males, n=17). RESULTS: After correction for multiple testing, we observed that circulating levels of 11-deoxycortisol, 17α-hydroxyprogesterone in females, and progesterone in males were significantly different between HC, ME/CFSmm, and ME/CFSsa. Comparing two independent groups, we found that female ME/CFSsa had higher levels of 11-deoxycortisol (vs. HC and ME/CFSmm) and 17α-hydroxyprogesterone (vs. HC). In addition, female ME/CFSmm showed a significant increase in progesterone levels compared to HC. In contrast, our study found that male ME/CFSmm had lower circulating levels of cortisol and corticosterone, while progesterone levels were elevated compared to HC. In addition to these univariate analyses, our correlational and multivariate approaches identified differential associations between our study groups. Also, using two-component partial least squares discriminant analysis (PLS-DA), we were able to discriminate ME/CFS from HC with an accuracy of 0.712 and 0.846 for females and males, respectively. CONCLUSION: Our findings suggest the potential value of including steroid hormones in future studies aimed at improving stratification in ME/CFS. Additionally, our results provide new perspectives to explore the clinical relevance of these differences within specific patient subgroups.

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.

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.

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.

Slight pH Fluctuations in the Gold Nanoparticle Synthesis Process Influence the Performance of the Citrate Reduction Method.

Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities, and size-dependent optical properties. The most commonly used method for AuNP synthesis in aqueous solution is the reduction of tetrachloroauric acid (HAuCl4) with trisodium citrate. We have observed variations in the pH and in the concentration of the gold colloidal suspension synthesized under standard conditions, verifying a reduction in the reaction yield by around 46% from pH 5.3 (2.4 nM) to pH 4.7 (1.29 nM). Citrate-capped AuNPs were characterized by UV-visible spectroscopy, TEM, EDS, and zeta-potential measurements, revealing a linear correlation between pH and the concentration of the generated AuNPs. This result can be attributed to the adverse effect of protons both on citrate oxidation and on citrate adsorption onto the gold surface, which is required to form the stabilization layer. Overall, this study provides insight into the effect of the pH over the synthesis performance of the method, which would be of particular interest from the point of view of large-scale manufacturing processes.

Insulin requires normal expression and signaling of insulin receptor A to reverse gestational diabetes-reduced adenosine transport in human umbilical vein endothelium.

Reduced adenosine uptake via human equilibrative nucleoside transporter 1 (hENT1) in human umbilical vein endothelial cells (HUVECs) from gestational diabetes mellitus (GDM) is reversed by insulin by restoring hENT1 expression. Insulin receptors A (IR-A) and B (IR-B) are expressed in HUVECs, and GDM results in higher IR-A mRNA expression vs. cells from normal pregnancies. We studied whether the reversal of GDM effects on transport by insulin depends on restoration of IR-A expression. We specifically measured hENT1 expression [mRNA, protein abundance, SLC29A1 (for hENT1) promoter activity] and activity (adenosine transport kinetics) and the role of IR-A/IR-B expression and signaling [total and phosphorylated 42 and 44 kDa mitogen-activated protein kinases (p44/42(mapk)) and Akt] in IR-A, IR-B, and IR-A/B knockdown HUVECs from normal (n = 33) or GDM (n = 33) pregnancies. GDM increases IR-A/IR-B mRNA expression (1.8-fold) and p44/42(mapk):Akt activity (2.7-fold) ratios. Insulin reversed GDM-reduced hENT1 expression and maximal transport capacity (V(max)/K(m)), and GDM-increased IR-A/IR-B mRNA expression and p44/42(mapk):Akt activity ratios to values in normal pregnancies. Insulin's effect was abolished in IR-A or IR-A/B knockdown cells. Thus, insulin requires normal IR-A expression and p44/42(mapk)/Akt signaling to restore GDM-reduced hENT1 expression and activity in HUVECs. This could be a protective mechanism for the placental macrovascular endothelial dysfunction seen in GDM.

Insulin requires A1 adenosine receptors expression to reverse gestational diabetes-increased L-arginine transport in human umbilical vein endothelium.

Gestational diabetes mellitus (GDM) associates with increased L-arginine transport and extracellular concentration of adenosine in human umbilical vein endothelial cells (HUVECs). In this study we aim to determine whether insulin reverses GDM-increased L-arginine transport requiring adenosine receptors expression in HUVECs. Primary cultured HUVECs from full-term normal (n = 38) and diet-treated GDM (n = 38) pregnancies were used. Insulin effect was assayed on human cationic amino acid transporter 1 (hCAT1) expression (protein, mRNA, SLC7A1 promoter activity) and activity (initial rates of L-arginine transport) in the absence or presence of adenosine receptors agonists or antagonists. A1 adenosine receptors (A1AR) and A2AAR expression (Western blot, quantitative PCR) was determined. Experiments were done in cells expressing or siRNA-suppressed expression of A1AR or A2AAR. HUVECs from GDM exhibit higher maximal transport capacity (maximal velocity (V max)/apparent Michaelis Menten constant (K m), V max/K m), which is blocked by insulin by reducing the V max to values in cells from normal pregnancies. Insulin also reversed the GDM-associated increase in hCAT-1 protein abundance and mRNA expression, and SLC7A1 promoter activity for the fragment -606 bp from the transcription start point. Insulin effects required A1AR, but not A2AAR expression and activity in this cell type. In the absence of insulin, GDM-increased hCAT-1 expression and activity required A2AAR expression and activity. HUVECs from GDM pregnancies exhibit a differential requirement of A1AR or A2AAR depending on the level of insulin, a phenomenon that represent a condition where adenosine or analogues of this nucleoside could be acting as helpers of insulin biological effects in GDM.

Role of insulin and adenosine in the human placenta microvascular and macrovascular endothelial cell dysfunction in gestational diabetes mellitus.

Microvascular and macrovascular endothelial function maintains vascular reactivity. Several diseases alter endothelial function, including hypertension, obesity, and diabetes mellitus. In addition, micro- and macrovascular endothelial dysfunction is documented in GDM with serious consequences for the growing fetus. Increased l-arginine uptake via hCAT-1 and NO synthesis by eNOS is associated with GDM. These alterations are paralleled by activation of purinergic receptors and increased umbilical vein, but not arteries blood adenosine accumulation. GDM associates with NO-reduced adenosine uptake in placental endothelium, suggested to maintain and/or facilitate insulin vasodilation likely increasing hCAT-1 and eNOS expression and activity. It is proposed that increased umbilical vein blood adenosine concentration in GDM reflects a defective metabolic state of human placenta. In addition, insulin recovers GDM-alterations in hCAT-1 and eNOS in human micro- and macrovascular endothelium, and its biological actions depend on preferential activation of insulin receptors A and B restoring a normal-like from a GDM-like phenotype. We summarized existing evidence for a potential role of insulin/adenosine/micro- and macrovascular endothelial dysfunction in GDM. These mechanisms could be crucial for a better management of the mother, fetus and newborn in GDM pregnancies.

Maternal hypercholesterolemia in pregnancy associates with umbilical vein endothelial dysfunction: role of endothelial nitric oxide synthase and arginase II.

OBJECTIVE: Human pregnancy that courses with maternal supraphysiological hypercholesterolemia (MSPH) correlates with atherosclerotic lesions in fetal arteries. It is known that hypercholesterolemia associates with endothelial dysfunction in adults, a phenomenon where nitric oxide (NO) and arginase are involved. However, nothing is reported on potential alterations in the fetoplacental endothelial function in MSPH. The aim of this study was to determine whether MSPH alters fetal vascular reactivity via endothelial arginase/urea and L-arginine transport/NO signaling pathways. APPROACH AND RESULTS: Total cholesterol <280 mg/dL was considered as maternal physiological hypercholesterolemia (n=46 women) and ≥ 280 mg/dL as MSPH (n=28 women). Maternal but not fetal total cholesterol and low-density lipoprotein-cholesterol levels were elevated in MSPH. Umbilical veins were used for vascular reactivity assays (wire myography), and primary cultures of umbilical vein endothelial cells to determine arginase, endothelial NO synthase (eNOS), and human cationic amino acid transporter 1 and human cationic amino acid transporter 2A/B expression and activity. MSPH reduced calcitonine gene-related peptide-umbilical vein relaxation and increased intima/media ratio (histochemistry), as well as reduced eNOS activity (L-citrulline synthesis from L-arginine, eNOS phosphorylation/dephosphorylation), but increased arginase activity and arginase II protein abundance. Arginase inhibition increased eNOS activity and L-arginine transport capacity without altering human cationic amino acid transporter 1 or human cationic amino acid transporter 2A/B protein abundance in maternal physiological hypercholesterolemia and MSPH. CONCLUSIONS: MSPH is a pathophysiological condition altering umbilical vein reactivity because of fetal endothelial dysfunction associated with arginase and eNOS signaling imbalance. We speculate that elevated maternal circulating cholesterol is a factor leading to fetal endothelial dysfunction, which could have serious consequences to the growing fetus.

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.

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.

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.

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.

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.

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.

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.

Insulin-stimulated L-arginine transport requires SLC7A1 gene expression and is associated with human umbilical vein relaxation.

Insulin causes endothelium-derived nitric oxide (NO)-dependent vascular relaxation, and increases L-arginine transport via cationic amino acid transporter 1 (hCAT-1) and endothelial NO synthase (eNOS) expression and activity in human umbilical vein endothelium (HUVEC). We studied insulin effect on SLC7A1 gene (hCAT-1) expression and hCAT-transport activity role in insulin-modulated human fetal vascular reactivity. HUVEC were used for L-arginine transport and L-[(3) H]citrulline formation (NOS activity) assays in absence or presence of N-ethylmaleimide (NEM) or L-lysine (L-arginine transport inhibitors). hCAT-1 protein abundance was estimated by Western blot, mRNA quantification by real time PCR, and SLC7A1 promoter activity by Luciferase activity (-1,606 and -650 bp promoter fragments from ATG). Specific protein 1 (Sp1), and total or phosphorylated eNOS protein was determined by Western blot. Sp1 activity (at four sites between -177 and -105 bp from ATG) was assayed by chromatin immunoprecipitation (ChIP) and vascular reactivity in umbilical vein rings. Insulin increased hCATs-L-arginine transport, maximal transport capacity (V(max) /K(m) ), and hCAT-1 expression. NEM and L-lysine blocked L-arginine transport. In addition, it was trans-stimulated (∼7.8-fold) by L-lysine in absence of insulin, but unaltered (~1.4-fold) in presence of insulin. Sp1 nuclear protein abundance and binding to DNA, and SLC7A1 promoter activity was increased by insulin. Insulin increased NO synthesis and caused endothelium-dependent vessel relaxation and reduced U46619-induced contraction, effects blocked by NEM and L-lysine, and dependent on extracellular L-arginine. We suggest that insulin induces human umbilical vein relaxation by increasing HUVEC L-arginine transport via hCATs (likely hCAT-1) most likely requiring Sp1-activated SLC7A1 expression.

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.

Role of proteases in dysfunctional placental vascular remodelling in preeclampsia.

Preeclampsia is a syndrome characterised by vascular dysfunction, impaired angiogenesis, and hypertension during pregnancy. Even when the precise pathophysiology of preeclampsia remains elusive, impaired vascular remodelling and placental angiogenesis in the placental villi and defective trophoblast invasion of the uterus are proposed as crucial mechanisms in this syndrome. Reduced trophoblast invasion leads to reduced uteroplacental blood flow and oxygen availability and increased oxidative stress. These phenomena trigger the release of soluble factors into the maternal and foetoplacental circulation that are responsible of the clinical features of preeclampsia. New blood vessels generation as well as vascular remodelling are mechanisms that require expression and activity of different proteases, including matrix metalloproteases, a-disintegrin and metalloproteases, and a-disintegrin and metalloprotease with thrombospondin motifs. These proteases exert proteolysis of the extracellular matrix. Additionally, cathepsins, a family of proteolytic enzymes, are primarily located in lysosomes but are also released by cells to the extracellular space. This review focuses on the role that these proteases play in the regulation of the uterine trophoblast invasion and the placental vascular remodelling associated with preeclampsia.

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.