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Objective: To compare the predictive performance of three different mathematical models for first‐trimester screening of pre‐eclampsia (PE), which combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI) and serum placental growth factor (PlGF), and two risk‐scoring systems. Methods: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with singleton pregnancy and a non‐malformed live fetus attending their routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate in the study. Maternal characteristics and medical history were recorded and measurements of MAP, UtA‐PI, serum PlGF and pregnancy‐associated plasma protein‐A (PAPP‐A) were converted into multiples of the median (MoM). Risks for term PE, preterm PE (< 37 weeks' gestation) and early PE (< 34 weeks' gestation) were calculated according to the FMF competing‐risks model, the Crovetto et al. logistic regression model and the Serra et al. Gaussian model. PE classification was also performed based on the recommendations of the National Institute for Health and Care Excellence (NICE) and the American College of Obstetricians and Gynecologists (ACOG). We estimated detection rates (DR) with their 95% CIs at a fixed 10% screen‐positive rate (SPR), as well as the area under the receiver‐operating‐characteristics curve (AUC) for preterm PE, early PE and all PE for the three mathematical models. For the scoring systems, we calculated DR and SPR. Risk calibration was also assessed. Results: The study population comprised 10 110 singleton pregnancies, including 32 (0.3%) that developed early PE, 72 (0.7%) that developed preterm PE and 230 (2.3%) with any PE. At a fixed 10% SPR, the FMF, Crovetto et al. and Serra et al. models detected 82.7% (95% CI, 69.6–95.8%), 73.8% (95% CI, 58.7–88.9%) and 79.8% (95% CI, 66.1–93.5%) of early PE; 72.7% (95% CI, 62.9–82.6%), 69.2% (95% CI, 58.8–79.6%) and 74.1% (95% CI, 64.2–83.9%) of preterm PE; and 55.1% (95% CI, 48.8–61.4%), 47.1% (95% CI, 40.6–53.5%) and 53.9% (95% CI, 47.4–60.4%) of all PE, respectively. The best correlation between predicted and observed cases was achieved by the FMF model, with an AUC of 0.911 (95% CI, 0.879–0.943), a slope of 0.983 (95% CI, 0.846–1.120) and an intercept of 0.154 (95% CI, –0.091 to 0.397). The NICE criteria identified 46.7% (95% CI, 35.3–58.0%) of preterm PE at 11% SPR and ACOG criteria identified 65.9% (95% CI, 55.4–76.4%) of preterm PE at 33.8% SPR. Conclusions: The best performance of screening for preterm PE is achieved by mathematical models that combine maternal factors with MAP, UtA‐PI and PlGF, as compared to risk‐scoring systems such as those of NICE and ACOG. While all three algorithms show similar results in terms of overall prediction, the FMF model showed the best performance at an individual level. © 2024 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Objective: Effective first‐trimester screening for pre‐eclampsia (PE) can be achieved using a competing‐risks model that combines risk factors from the maternal history with multiples of the median (MoM) values of biomarkers. A new model using artificial intelligence through machine‐learning methods has been shown to achieve similar screening performance without the need for conversion of raw data of biomarkers into MoM. This study aimed to investigate whether this model can be used across populations without specific adaptations. Methods: Previously, a machine‐learning model derived with the use of a fully connected neural network for first‐trimester prediction of early (< 34 weeks), preterm (< 37 weeks) and all PE was developed and tested in a cohort of pregnant women in the UK. The model was based on maternal risk factors and mean arterial blood pressure (MAP), uterine artery pulsatility index (UtA‐PI), placental growth factor (PlGF) and pregnancy‐associated plasma protein‐A (PAPP‐A). In this study, the model was applied to a dataset of 10 110 singleton pregnancies examined in Spain who participated in the first‐trimester PE validation (PREVAL) study, in which first‐trimester screening for PE was carried out using the Fetal Medicine Foundation (FMF) competing‐risks model. The performance of screening was assessed by examining the area under the receiver‐operating‐characteristics curve (AUC) and detection rate (DR) at a 10% screen‐positive rate (SPR). These indices were compared with those derived from the application of the FMF competing‐risks model. The performance of screening was poor if no adjustment was made for the analyzer used to measure PlGF, which was different in the UK and Spain. Therefore, adjustment for the analyzer used was performed using simple linear regression. Results: The DRs at 10% SPR for early, preterm and all PE with the machine‐learning model were 84.4% (95% CI, 67.2–94.7%), 77.8% (95% CI, 66.4–86.7%) and 55.7% (95% CI, 49.0–62.2%), respectively, with the corresponding AUCs of 0.920 (95% CI, 0.864–0.975), 0.913 (95% CI, 0.882–0.944) and 0.846 (95% CI, 0.820–0.872). This performance was achieved with the use of three of the biomarkers (MAP, UtA‐PI and PlGF); inclusion of PAPP‐A did not provide significant improvement in DR. The machine‐learning model had similar performance to that achieved by the FMF competing‐risks model (DR at 10% SPR, 82.7% (95% CI, 69.6–95.8%) for early PE, 72.7% (95% CI, 62.9–82.6%) for preterm PE and 55.1% (95% CI, 48.8–61.4%) for all PE) without requiring specific adaptations to the population. Conclusions: A machine‐learning model for first‐trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations. However, before doing so, it is essential to make adjustments for the analyzer used for biochemical testing. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic accuracy of the Fetal Medicine Foundation (FMF) competing‐risks model, incorporating maternal characteristics, mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI) and placental growth factor (PlGF) (the 'triple test'), for the prediction at 11–13 weeks' gestation of preterm pre‐eclampsia (PE) in a Spanish population. Methods: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with a singleton pregnancy and a non‐malformed live fetus attending a routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate. Maternal demographic characteristics and medical history were recorded and MAP, UtA‐PI, serum PlGF and pregnancy‐associated plasma protein‐A (PAPP‐A) were measured following standardized protocols. Treatment with aspirin during pregnancy was also recorded. Raw values of biomarkers were converted into multiples of the median (MoM), and audits were performed periodically to provide regular feedback to operators and laboratories. Patient‐specific risks for term and preterm PE were calculated according to the FMF competing‐risks model, blinded to pregnancy outcome. The performance of screening for PE, taking into account aspirin use, was assessed by calculating the area under the receiver‐operating‐characteristics curve (AUC) and detection rate (DR) at a 10% fixed screen‐positive rate (SPR). Risk calibration of the model was assessed. Results: The study population comprised 10 110 singleton pregnancies, including 72 (0.7%) that developed preterm PE. In the preterm PE group, compared to those without PE, median MAP MoM and UtA‐PI MoM were significantly higher, and median serum PlGF MoM and PAPP‐A MoM were significantly lower. In women with PE, the deviation from normal in all biomarkers was inversely related to gestational age at delivery. Screening for preterm PE by a combination of maternal characteristics and medical history with MAP, UtA‐PI and PlGF had a DR, at 10% SPR, of 72.7% (95% CI, 62.9–82.6%). An alternative strategy of replacing PlGF with PAPP‐A in the triple test was associated with poorer screening performance for preterm PE, giving a DR of 66.5% (95% CI, 55.8–77.2%). The calibration plot showed good agreement between predicted risk and observed incidence of preterm PE, with a slope of 0.983 (95% CI, 0.846–1.120) and an intercept of 0.154 (95% CI, −0.091 to 0.397). Conclusions: The FMF model is effective in predicting preterm PE in the Spanish population at 11–13 weeks' gestation. This method of screening is feasible to implement in routine clinical practice, but it should be accompanied by a robust audit and monitoring system, in order to maintain high‐quality screening. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

This article compares the predictive performance of three different mathematical models for screening pre-eclampsia (PE) in the first trimester of pregnancy. The models combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtPI), and serum placental growth factor (PlGF). The study, conducted in eight Spanish hospitals, included 10,110 singleton pregnancies. The results showed that all three models had similar overall prediction results and outperformed the scoring systems. However, the FMF model demonstrated the best performance at the individual level. [Extracted from the article]

Effluents of wastewater treatment plants can abundantly spread endocrine disrupting chemicals in the environment. To improve water quality monitoring, the use of effect-based tools that measure estrogenic activity has been suggested, however their results could be influenced by different factors. This study compared the estrogenic activity of wastewater samples extracted with two stationary phases and tested with two in vitro effect-based assays to investigate whether and how stationary phases and assays could influence biomonitoring data. During four seasonal periods, the effluents of six WWTPs located in northern Italy were sampled. After the extraction using two different stationary phases (HLB, C18), the samples (n = 72) were tested using two effect-based assays: a gene reporter luciferase assay on mammalian cells (MELN) and yeast estrogen screen assay (YES). The results showed that estrogenic activity of HLB extracts was significantly different from the activity of C18 extracts, suggesting that extraction phase can influence biomonitoring data. Moreover, the estrogenic activity was overall higher using gene reporter MELN assay than using YES assay, suggesting that, due to difference in cell membrane permeability and metabolic activation, the applied cell model can affect the biomonitoring results. Finally, from the comparison between the activity of the final effluent and the environmentally safe estrogenic levels in surface waters, MELN data suggested that the activity of this effluent may pose an environmental risk, while YES data showed that it should not be considered a threat to the receiving surface waters. This study pointed out that a standardized approach is needed to assess the estrogenic activity of waters; it reported important data to select the most suitable stationary phase for samples extraction (samples extracted with C18 sorbent showed higher estradiol equivalent concentration values) and the most appropriate bioassay (gene reporter luciferase MELN assay was more sensitive than YES assay) to assess the environmental risk, thus protecting human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The discovery of ferroelectricity in the fluorite structure based hafnium oxide (HfO 2 ) material sparked major efforts for reviving the ferroelectric field effect transistor (FeFET) memory concept. A Novel metal-ferroelectric-metal-ferroelectric-insulator-semiconductor (MFMFIS) FeFET memory is reported based on dual ferroelectric integration as an MFM and MFIS in a single gate stack using Si-doped Hafnium oxide (HSO) ferroelectric (FE) material. The MFMFIS top and bottom electrode contacts, dual HSO based ferroelectric layers, and tailored MFM to MFIS area ratio (AR-TB) provide a flexible stack structure tuning for improving the FeFET performance. The AR-TB tuning shows a tradeoff between the MFM voltage increase and the weaker FET Si channel inversion, particularly notable in the drain saturation current I D (sat) when the AR-TB ratio decreases. Dual HSO ferroelectric layer integration enables a maximized memory window (MW) and dynamic control of its size by tuning the MFM to MFIS switching contribution through the AR-TB change. The stack structure control via the AR-TB tuning shows further merits in terms of a low voltage switching for a saturated MW size, an extremely linear at wide dynamic range of the current update, as well as high symmetry in the long term synaptic potentiation and depression. The MFMFIS stack reliability is reported in terms of the switching variability, temperature dependence, endurance, and retention. The MFMFIS concept is thoroughly discussed revealing profound insights on the optimal MFMFIS stack structure control for enhancing the FeFET memory performance., (Creative Commons Attribution license.)

Objectives: First, to determinate the frequency of chorioamnionitis and funisitis in cases of intramniotic detection of Ureaplasma urealyticum. Second, to assess the predictive capability of some biological markers in the amniotic fluid of these women to predict histological inflammation., Subjects and Methods: We prospectively studied 20 cases of women with premature rupture of membranes or preterm labour (PROM) or preterm labour and intraamniotic detection of Ureaplasma urealyticum. Gestational age at admission was 26.74 ± 2.53 weeks. Amniotic fluid concentrations of IL18, IL 2, IL4, IL6, IL10, IL12, TNF-alpha, IFN-g, and MMP-8 were measured by the Multiplex method. Amniotic fluid glucose and leukocyte count were also measured by standard methods. Placental detailed histological studies were performed. Student's t-test, forward stepwise conditional binary logistic regression analysis and ROC curves were used., Results: Histological chorioamnionitis was present in 45% of cases (9/20) and funisitis just in 15% (3/20). Interleukins 6, 8, 12, MMP-8, and leukocyte count were significantly elevated in cases of histological inflammation, defined as choriamnionitis or chorioamniotis + funisitis (p = .007, .03, .01, .03, .03, respectively) while glucose was decreased (p = .04). Binary logistic regression for the prediction of inflammation showed a high predictive value (R 2  = .66, p = .002) including in the equation only the IL6 value., Conclusions: A significant percentage of cases with intraamniotic detection of Ureaplasma urealyticum shows no pathological signs of histological inflammation. Concentration of Interleukin 6 in amniotic fluid can be useful for the diagnosis of subclinical chorioamnionitis in these cases.

Objectives: To evaluate whether the amniotic fluid (AF) cytokine profile in women with chorioamnionitis may differentiate between those with and without funisitis., Subjects and Methods: Forty women at high risk of chorioamnionitis were studied. Gestational age at study was 26.94. Amniocentesis, universal and specific polymerase chain reaction, and microbiological cultures were performed. AF IL-1β, IL-2, IL-4, IL-6, IL 8, IL-10, IL-12, TNF-alpha, IFN-gamma, and MMP-8 were measured by multiplex assay. After delivery, the placenta and umbilical cord were studied histologically. Comparisons were made between three groups: controls, and chorioamnionitis with and without funisitis., Results: In 25 cases, the histological findings were normal (61.5%). The remaining 15 composed of 9 cases of chorioamnionitis alone (9/40; 23.1%) and 6 cases of chorioamnionitis plus funisitis (6/40; 15.4%). All AF cytokine levels were significantly higher in the cases with chorioamnionitis in comparison to controls, except for IFN-gamma. The comparisons between the three groups showed significant differences between chorioamnionitis alone and chorioamnionitis plus funisitis in IL-1β, IL-6, IL-10, IL-12, IL-8, and TNF-alpha, with the levels being higher when funisitis was present. Logistic regression found a powerful predictive model for funisitis including the following cytokinesIL-4, IL-10, IL-12, and IL-8., Conclusions: Measurements of AF interleukins 4, 10, 12, and 8 allow to identify cases with funisitisin women at high risk of chorioamnionitis.

Chorioamnionitis is a complication of pregnancy associated with significant maternal and perinatal long-term adverse outcomes. We apply high-throughput amniotic fluid (AF) metabolomics analysis for better understanding the pathophysiological mechanism of chorioamnionitis and its associated perinatal neurological injury and to provide meaningful information about new potential biomarkers. AF samples (n = 40) were collected from women at risk of chorioamnionits. Detailed clinical information on each pregnancy was obtained from obstetrical and neonatal medical examination. Liquid chromatography (LC)/mass spectrometry (MS) followed by data alignment and filtration as well as univariate and multivariate statistical analysis was performed. Statistically significant differences were found in 60 masses in positive and 115 in negative ionization mode obtained with LC/quadrupole time-of-flight MS (LC-QTOF-MS) between women with and without chorioamnionitis. Identified compounds were mainly related to glycerophospholipids and sphingolipids metabolism. From them, LPE(16:0)/LPE(P-16:0) and especially lactosylceramides emerged as the best biomarker candidates. Sulfocholic acid, trioxocholenoic acids, and LPC(18:2) were particularly increased in women with chorioamnionitis whose newborns developed perinatal brain damage. Therefore, we propose LPE(16:0)/LPE(P-16:0) and lactosylceramides as biomarkers for chorioamnionitis as well as LPC(18:2), trioxocholenoic acid, and sulfocholic acid for its associated perinatal brain damage. Metabolomics fingerprinting of AF enables the prediction of pregnancy-related disorders and the development of new diagnostics strategies.

Aims: Breast cancer is the most frequently diagnosed cancer among women. Up to 50% of breast cancer cases occur in patients over the age of 65 years. Hormonal therapy as a single alternative treatment has been used in this population. The aim of this study was to analyze the oncological outcomes in breast cancer patients who received hormonal therapy alone as a primary treatment., Methods: We retrospectively reviewed our database to find all patients with breast cancer from 2006 to 2011 who were treated with hormonal therapy only at our center. The collected data included patients and tumor characteristics, type of drug administered, follow-up details and type of response obtained using RECIST criteria., Results: We included 44 breast cancer patients. The mean age was 83.5 ± 6.0 years. The majority of patients had tumors with less aggressive immunohistochemical characteristics and 100% of them presented positive estrogen receptors. The pharmacological treatment included exemestane, anastrozole, tamoxifen, letrozole and fulvestrant. The effectiveness rate was 60%, evaluated according to tumor reduction or no progression., Conclusion: The efficacy of hormonal therapy in older patients is reasonably high to justify its use in selected patients. Therefore, it is a sensible alternative for patients who refuse or are unfit for surgery., (© 2014 S. Karger AG, Basel.)

Introduction: Gastrointestinal stromal tumors are very rare, representing 0.1% to 1% of gastrointestinal malignancies. Gastrointestinal stromal tumors outside the digestive tract comprise a very small fraction of all gastrointestinal stromal tumors, and their most common locations are the omentum, the mesentery, and, in few cases, the rectovaginal septum. Despite their low incidence, extragastrointestinal stromal tumors are potentially malignant tumors and they present a high rate of recurrences. This, added to the fact that they are often asymptomatic until advanced stages, determines an unfavorable prognosis., Case Report: We report a case of gastrointestinal stromal tumor located in the rectovaginal septum, which recurred after local excision; hence, a reintervention was needed., Conclusions: A correct differential diagnosis between extragastrointestinal stromal tumors and other similar pathologies such as leiomyomas or schwannomas is imperative based on their histology and immunohistochemistry. The correct diagnosis of extragastrointestinal stromal tumors allows to start adequate treatment and follow-up, preventing recurrence that determines their poor prognosis.

Background: During the last ten years multiple pregnancies have been increased as a result of assisted reproduction techniques, increases of even 470% are published. Multiple pregnancies are related to a higher risk of maternal and neonatal morbidity and mortality, as well as to increased use of health resources., Objectives: To review the fetal and perinatal early complications in triple pregnancies., Patients and Method: An observational and retrospective study of triple pregnancies followed up at the Obstetrics Department of La Paz University Hospital, Madrid, Spain, from January 2000 until May 2011., Results: We reviewed the medical records of 147 triplets. The prevalence of triplets was 1 in 640 deliveries (0.15%). Among all, 79% were achieved using assisted reproductive techniques, 73% were obtained by means of in vitro fertilization. Regarding the pregnancy zigosity we found: 85% trichorionic triamniotic, 10% bichorionic triamniotic and 5% monochorionic tramniotic. Out of 402 fetuses, 35 (9%) had the following complications: 19(5%) growth retardation or oligohydramnios, nine (2%) intrauterine death, three (0.74%) postnatal death due to suspected chorioamnionitis, three (0.74%) major malformations and one case (0.24%) of twin to twin transfusion. The average duration of gestation was 33 weeks: 8% were born before 28 weeks of gestation, 30% between 28 and 32 weeks and 62% after 32 weeks. The mean birth weight was 1,906 +/- 400 g. In 29 cases (7%) arterial pH was less than 7.20. Any type of resuscitation was required by 60% of newborns and 47% were admitted to the intensive care unit. There were no significant differences in neonatal early outcomes among the first, second and third newborn., Conclusions: The risk of neonatal mortality and morbidity seems to be higher in triple pregnancies. Adverse neonatal outcomes are related to the high rate of severe prematurity.

Objectives: To evaluate the incidence and characteristics of maternal complications in triple pregnancies. An additional objective was to study the relation between assisted reproductive techniques and maternal complications., Material and Methods: Retrospective study on 147 triplets assisted at the Gynecology and Obstetrics department of La Paz University Hospital between 2000 and 2010. We analyzed the incidence of maternal complications and their relation to assisted reproductive techniques., Results: One triplet was observed every 711 pregnancies. The most frequent maternal complications were spontaneous preterm labor (56%), premature rupture of membranes (28.9%), anemia (24.4%) and preeclampsia (20.4%). Triplets conceived by assisted reproductive techniques were significantly more likely to develop spontaneous preterm labor than spontaneous pregnancies (60% vs. 40%, respectively; p = 0.045)., Conclusions: Triplets have a very high risk of maternal complications such as preeclampsia. Moreover, the presence of spontaneous preterm labor is more frequent in triplets conceived by assisted reproductive techniques than in those spontaneously conceived.