Microbiome signatures of progression toward celiac disease onset in at-risk children in a longitudinal prospective cohort study.

Other than exposure to gluten and genetic compatibility, the gut microbiome has been suggested to be involved in celiac disease (CD) pathogenesis by mediating interactions between gluten/environmental factors and the host immune system. However, to establish disease progression markers, it is essential to assess alterations in the gut microbiota before disease onset. Here, a prospective metagenomic analysis of the gut microbiota of infants at risk of CD was done to track shifts in the microbiota before CD development. We performed cross-sectional and longitudinal analyses of gut microbiota, functional pathways, and metabolites, starting from 18 mo before CD onset, in 10 infants who developed CD and 10 matched nonaffected infants. Cross-sectional analysis at CD onset identified altered abundance of six microbial strains and several metabolites between cases and controls but no change in microbial species or pathway abundance. Conversely, results of longitudinal analysis revealed several microbial species/strains/pathways/metabolites occurring in increased abundance and detected before CD onset. These had previously been linked to autoimmune and inflammatory conditions (e.g., Dialister invisus, Parabacteroides sp., Lachnospiraceae, tryptophan metabolism, and metabolites serine and threonine). Others occurred in decreased abundance before CD onset and are known to have anti-inflammatory effects (e.g., Streptococcus thermophilus, Faecalibacterium prausnitzii, and Clostridium clostridioforme). Additionally, we uncovered previously unreported microbes/pathways/metabolites (e.g., Porphyromonas sp., high mannose-type N-glycan biosynthesis, and serine) that point to CD-specific biomarkers. Our study establishes a road map for prospective longitudinal study designs to better understand the role of gut microbiota in disease pathogenesis and therapeutic targets to reestablish tolerance and/or prevent autoimmunity.

A screening test proposal for congenital defects based on maternal serum metabolomics profile.

BACKGROUND: Historically, noninvasive techniques are only able to identify chromosomal anomalies that accounted for <50% of all congenital defects; the other congenital defects are diagnosed via ultrasound evaluations in the later stages of pregnancy. Metabolomic analysis may provide an important improvement, potentially addressing the need for novel noninvasive and multicomprehensive early prenatal screening tools. A growing body of evidence outlines notable metabolic alterations in different biofluids derived from pregnant women carrying fetuses with malformations, suggesting that such an approach may allow the discovery of biomarkers common to most fetal malformations. In addition, metabolomic investigations are inexpensive, fast, and risk-free and often generate high performance screening tests that may allow early detection of a given pathology. OBJECTIVE: This study aimed to evaluate the diagnostic accuracy of an ensemble machine learning model based on maternal serum metabolomic signatures for detecting fetal malformations, including both chromosomal anomalies and structural defects. STUDY DESIGN: This was a multicenter observational retrospective study that included 2 different arms. In the first arm, a total of 654 Italian pregnant women (334 cases with fetuses with malformations and 320 controls with normal developing fetuses) were enrolled and used to train an ensemble machine learning classification model based on serum metabolomics profiles. In the second arm, serum samples obtained from 1935 participants of the New Zealand Screening for Pregnancy Endpoints study were blindly analyzed and used as a validation cohort. Untargeted metabolomics analysis was performed via gas chromatography-mass spectrometry. Of note, 9 individual machine learning classification models were built and optimized via cross-validation (partial least squares-discriminant analysis, linear discriminant analysis, naïve Bayes, decision tree, random forest, k-nearest neighbor, artificial neural network, support vector machine, and logistic regression). An ensemble of the models was developed according to a voting scheme statistically weighted by the cross-validation accuracy and classification confidence of the individual models. This ensemble machine learning system was used to screen the validation cohort. RESULTS: Significant metabolic differences were detected in women carrying fetuses with malformations, who exhibited lower amounts of palmitic, myristic, and stearic acids; N-α-acetyllysine; glucose; L-acetylcarnitine; fructose; para-cresol; and xylose and higher levels of serine, alanine, urea, progesterone, and valine (P<.05), compared with controls. When applied to the validation cohort, the screening test showed a 99.4%±0.6% accuracy (specificity of 99.9%±0.1% [1892 of 1894 controls correctly identified] with a sensitivity of 78%±6% [32 of 41 fetal malformations correctly identified]). CONCLUSION: This study provided clinical validation of a metabolomics-based prenatal screening test to detect the presence of congenital defects. Further investigations are needed to enable the identification of the type of malformation and to confirm these findings on even larger study populations.

Screening performances of an 8-item UPSIT Italian version in the diagnosis of Parkinson's disease.

Hyposmia is a common finding in Parkinson's disease (PD) and is usually tested through the University of Pennsylvania Smell Identification Test (UPSIT). The aim of our study is to provide a briefer version of the Italian-adapted UPSIT test, able to discriminate between PD patients and healthy subjects (HS). By means of several univariate and multivariate (machine-learning-based) statistical approaches, we selected 8 items by which we trained a partial-least-square discriminant analysis (PLS-DA) and a decision tree (DT) model: class predictions of both models performed better with the 8-item version when compared to the 40-item version. An area under the receiver operating characteristic (AUC-ROC) curve built with the selected 8 odors showed the best performance (sensitivity 86.8%, specificity 82%) in predicting the PD condition at a cut-off point of ≤ 6. These performances were higher than those previously calculated for the 40-item UPSIT test (sensitivity 82% and specificity 88.2 % with a cut-off point of ≤ 21). Qualitatively, our selection contains one odor (i.e., apple) which is Italian-specific, supporting the need for cultural adaptation of smell testing; on the other hand, some of the selected best discriminating odors are in common with existing brief smell test versions validated on PD patients of other cultures, supporting the view that disease-specific odor patterns may exist and deserve a further evaluation.

A Systematic Review on Metabolomics Analysis in Hearing Impairment: Is It a Possible Tool in Understanding Auditory Pathologies?

With more than 466 million people affected, hearing loss represents the most common sensory pathology worldwide. Despite its widespread occurrence, much remains to be explored, particularly concerning the intricate pathogenic mechanisms underlying its diverse phenotypes. In this context, metabolomics emerges as a promising approach. Indeed, lying downstream from molecular biology's central dogma, the metabolome reflects both genetic traits and environmental influences. Furthermore, its dynamic nature facilitates well-defined changes during disease states, making metabolomic analysis a unique lens into the mechanisms underpinning various hearing impairment forms. Hence, these investigations may pave the way for improved diagnostic strategies, personalized interventions and targeted treatments, ultimately enhancing the clinical management of affected individuals. In this comprehensive review, we discuss findings from 20 original articles, including human and animal studies. Existing literature highlights specific metabolic changes associated with hearing loss and ototoxicity of certain compounds. Nevertheless, numerous critical issues have emerged from the study of the current state of the art, with the lack of standardization of methods, significant heterogeneity in the studies and often small sample sizes being the main limiting factors for the reliability of these findings. Therefore, these results should serve as a stepping stone for future research aimed at addressing the aforementioned challenges.

Metabolomics signatures of acutely ill and short-term weight recovered women with anorexia nervosa.

Although metabolomics studies are recently spreading and have allowed the characterization of putative biomarkers in many diseases, they are relatively scanty in anorexia nervosa (AN). In this explorative study we analyzed the fecal metabolomics profiles of women with AN in the underweight phase (n = 24) and after short-term weight restoration (n = 16) and compared them with 20 healthy women. An untargeted metabolomic procedure allowed the characterization of 224 metabolites involved in energy, lipid, and amino acid metabolism. A partial least square discriminant analysis identified 14 metabolites with a variable importance in projection score >1.5 that clearly differentiated underweight from weight-restored patients from healthy women. Compared with healthy women, fecal concentrations of valeric acid and 3-methyl,2-ketobutyric acid were increased in both underweight and weight-restored patients; fecal concentrations of propionic acid, stearic acid, linolenic acid, methyl-galactoside, coprosterol, cycloserine, and lauric acid were increased while fecal levels of xylose, fucose, and rhamnose were decreased in underweight patients and normalized after weight-restoration; fecal concentrations of piperine, phenylalanine, butyric acid, and meso-erythritol-1 were decreased while fecal levels of hydroxystearic acid were increased in weight-restored but normal in underweight AN patients. All these changes point to peculiar fecal metabolomics profiles of acute and short-term weight restored AN patients. The value of these changes to improve our understanding of the pathophysiology of AN and to characterize potential biomarker targets for developing new treatment strategies needs further studies to be clarified.

Untargeted metabolomics as a diagnostic tool in NAFLD: discrimination of steatosis, steatohepatitis and cirrhosis.

INTRODUCTION: Non-Alcoholic Fatty Liver Disease encompasses a spectrum of diseases ranging from simple steatosis to steatohepatitis (or NASH), up to cirrhosis and hepatocellular carcinoma (HCC). The challenge is to recognize the more severe and/or progressive pathology. A reliable non-invasive method does not exist. Untargeted metabolomics is a novel method to discover biomarkers and give insights on diseases pathophysiology. OBJECTIVES: We applied metabolomics to understand if simple steatosis, steatohepatitis and cirrhosis in NAFLD patients have peculiar metabolites profiles that can differentiate them among each-others and from controls. METHODS: Metabolomics signatures were obtained from 307 subjects from two separated enrollments. The first collected samples from 69 controls and 144 patients (78 steatosis, 23 NASH, 15 NASH-cirrhosis, 8 HCV-cirrhosis, 20 cryptogenic cirrhosis). The second, used as validation-set, enrolled 44 controls and 50 patients (34 steatosis, 10 NASH and 6 NASH-cirrhosis).The "Partial-Least-Square Discriminant-Analysis"(PLS-DA) was used to reveal class separation in metabolomics profiles between patients and controls and among each class of patients, and to reveal the metabolites contributing to class differentiation. RESULTS: Several metabolites were selected as relevant, in particular:Glycocholic acid, Taurocholic acid, Phenylalanine, branched-chain amino-acids increased at the increase of the severity of the disease from steatosis to NASH, NASH-cirrhosis, while glutathione decreased (p < 0.001 for each). Moreover, an ensemble machine learning (EML) model was built (comprehending 10 different mathematical models) to verify diagnostic performance, showing an accuracy > 80% in NAFLD clinical stages prediction. CONCLUSIONS: Metabolomics profiles of NAFLD patients could be a useful tool to non-invasively diagnose NAFLD and discriminate among the various stages of the disease, giving insights into its pathophysiology.

Noninvasive screening for congenital heart defects using a serum metabolomics approach.

OBJECTIVE: Heart anomalies represent nearly one-third of all congenital anomalies. They are currently diagnosed using ultrasound. However, there is a strong need for a more accurate and less operator-dependent screening method. Here we report a metabolomics characterization of maternal serum in order to describe a metabolomic fingerprint representative of heart congenital anomalies. METHODS: Metabolomic profiles were obtained from serum of 350 mothers (280 controls and 70 cases). Nine classification models were built and optimized. An ensemble model was built based on the results from the individual models. RESULTS: The ensemble machine learning model correctly classified all cases and controls. Malonic, 3-hydroxybutyric and methyl glutaric acid, urea, androstenedione, fructose, tocopherol, leucine, and putrescine were determined as the most relevant metabolites in class separation. CONCLUSION: The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal heart anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the revelation of the associated metabolites and their respective biochemical pathways allows a better understanding of the overall pathophysiology of affected pregnancies.

Multi-Systemic Alterations by Chronic Exposure to a Low Dose of Bisphenol A in Drinking Water: Effects on Inflammation and NAD+-Dependent Deacetylase Sirtuin1 in Lactating and Weaned Rats.

Bisphenol A (BPA) is largely used as a monomer in some types of plastics. It accumulates in tissues and fluids and is able to bypass the placental barrier, affecting various organs and systems. Due to huge developmental processes, children, foetuses, and neonates could be more sensitive to BPA-induced toxicity. To investigate the multi-systemic effects of chronic exposure to a low BPA dose (100 µg/L), pregnant Wistar rats were exposed to BPA in drinking water during gestation and lactation. At weaning, newborn rats received the same treatments as dams until sex maturation. Free and conjugated BPA levels were measured in plasma and adipose tissue; the size of cerebral ventricles was analysed in the brain; morpho-functional and molecular analyses were carried out in the liver with a focus on the expression of inflammatory cytokines and Sirtuin 1 (Sirt1). Higher BPA levels were found in plasma and adipose tissue from BPA treated pups (17 PND) but not in weaned animals. Lateral cerebral ventricles were significantly enlarged in lactating and weaned BPA-exposed animals. In addition, apart from microvesicular steatosis, liver morphology did not exhibit any statistically significant difference for morphological signs of inflammation, hypertrophy, or macrovesicular steatosis, but the expression of inflammatory cytokines, Sirt1, its natural antisense long non-coding RNA (Sirt1-AS LncRNA) and histone deacetylase 1 (Hdac1) were affected in exposed animals. In conclusion, chronic exposure to a low BPA dose could increase the risk for disease in adult life as a consequence of higher BPA circulating levels and accumulation in adipose tissue during the neonatal period.

Metabolomics in endometrial cancer diagnosis: A systematic review.

INTRODUCTION: Endometrial cancer (EC) is the most common gynecological malignancy in the developed world. The prognosis of EC strongly depends on tumor stage, hence the importance of improving diagnosis. Metabolomics has recently appeared as a promising test for a non-invasive diagnosis of several diseases. Nevertheless, no metabolic marker has been approved for use in the routine practice. We aimed to provide an overview of metabolomics findings in the diagnosis of EC. MATERIAL AND METHODS: A systematic review was performed by searching eight electronic databases from their inception to October 2019 for studies assessing metabolomics in EC diagnosis. Extracted data included characteristics of patients and EC, serum concentration of metabolites in women with and without EC and its association with EC diagnosis, tumor behavior and pathological characteristics. RESULTS: Six studies with 732 women (356 cases and 376 controls) were included. Several metabolites were found able to predict the presence of EC, tumor behavior (progression and recurrence) and pathological characteristics (histotype, myometrial invasion and lymph vascular space invasion). CONCLUSIONS: Metabolomics might be suitable for a non-invasive diagnosis and screening of EC, offering the possibility to predict tumor behavior and pathological characteristics. Further studies are necessary to validate these results.

Variations in sleep associated with different types of hormonal contraceptives.

Progesterone and some of its metabolites are neuroactive steroids that affect sleep by increasing melatonin secretion and stimulating GABA-A receptors. The effect of progestogens in hormonal contraceptives on sleep has not been thoroughly investigated. This observational study assessed possible associations in sleep changes induced by estrogen-progestogens in contraceptives in 108 women between the ages of 20 and 50 years. We assessed mean nightly sleep time with a 31-day sleep diary, and subjective sleep quality with the five subjective subscores of the Pittsburgh Sleep Quality Index (PSQI). Included women were of childbearing age, healthy, sexually active and had been using a hormonal contraceptive method (pill, intrauterine system (IUS), subcutaneous implant, vaginal ring) for at least six months. Results were compared to a matched control group that did not use hormonal contraceptives. The longest mean nightly sleep time, compared to control (450 min), occurred in women who used progestogen-only oral contraception (510 min), followed by IUS delivery of levonorgestrel 13.5 mg (480 min) and oral ethinylestradiol 0.02/0.03 mg plus gestodene 0.075 mg (475 min). Global subjective sleep quality was influenced most by the administration of etonorgestrel 0.120 mg/ethinylestradiol 0.015 mg via the vaginal route. Our results show that low-doses of progestins affect various aspects of sleep, and that this is influenced by the route of administration.

A metabolomic signature of treated and drug-naïve patients with Parkinson's disease: a pilot study.

INTRODUCTION: About 90% of cases of Parkinson's disease (PD) are idiopathic and attempts to understand pathogenesis typically assume a multifactorial origin. Multifactorial diseases can be studied using metabolomics, since the cellular metabolome reflects the interplay between genes and environment. OBJECTIVE: The aim of our case-control study is to compare metabolomic profiles of whole blood obtained from treated PD patients, de-novo PD patients and controls, and to study the perturbations correlated with disease duration, disease stage and motor impairment. METHODS: We collected blood samples from 16 drug naïve parkinsonian patients, 84 treated parkinsonian patients, and 42 age matched healthy controls. Metabolomic profiles have been obtained using gas chromatography coupled to mass spectrometry. Multivariate statistical analysis has been performed using supervised models; partial least square discriminant analysis and partial least square regression. RESULTS: This approach allowed separation between discrete classes and stratification of treated patients according to continuous variables (disease duration, disease stage, motor score). Analysis of single metabolites and their related metabolic pathways revealed unexpected possible perturbations related to PD and underscored existing mechanisms that correlated with disease onset, stage, duration, motor score and pharmacological treatment. CONCLUSION: Metabolomics can be useful in pathogenetic studies and biomarker discovery. The latter needs large-scale validation and comparison with other neurodegenerative conditions.

Molecular effects of copper on the reproductive system of mytilus galloprovincialis.

This study aims to assess the effects induced by 24 hr exposure to a subtoxic copper concentration on the reproductive system (gonads, spermatozoa, and protamine-like [PL] proteins) of Mytilus galloprovincialis. Inductively coupled plasma-mass spectrometry indicated accumulation of this metal in gonads, spermatozoa, and PL proteins of exposed mussels. Further, real-time polymerase chain reaction analyses showed altered expression levels of mt10 and PL proteins genes in spermatozoa and gonads, respectively, of exposed mussels. Protamine-like proteins, which represent the main basic component of sperm chromatin of this organism, showed a higher DNA binding affinity and a different DNA binding mode in exposed mussels. Moreover, an increased amount of NaCl was required for the release from sperm nuclei of PL-III, the main PL protein component. Finally, PL proteins extracted from exposed mussels promoted DNA oxidative damage in the presence of H 2 O 2. These results demonstrate that the tolerable copper amount could also affect the properties of PL proteins and determine the negative effects on the reproductive system of this organism. These analyses could be useful to develop quick and efficient chromatin-based genotoxicity tests for pollution biomonitoring programs.

Placental concentrations of essential, toxic, and understudied metals and relationships with birth outcomes in Chattanooga, TN.

BACKGROUND: Comprehensive examinations of placental metal concentrations and correlations with infant parameters are under-investigated. Chattanooga, Tennessee's consistently high incidence of low birth weight and potential for metal exposure provides an ideal opportunity to investigate potential correlations. OBJECTIVES: To investigate the associations between a wide variety of metals in placental tissue and multiple infant parameters. METHODS: A total of 31 elements were screened via ICP-MS in 374 individual placental samples. Of those, 14 were quantifiable in > 86% of the samples. We examined correlations between metal concentrations and infant parameters (birth weight, gestational age, birth weight centile, placental weight, birth length and head circumference). We fit multivariable regression models to estimate the covariate-adjusted associations of birth weight with ln-transformed concentrations of each of the 14 metals and used generalized additive models to examine nonlinear relationships. RESULTS: Some of the strongest relationships with infant parameters came from several lesser-studied metals. Placental rhodium concentrations were negatively correlated with almost all infant parameters. In the fully adjusted regression model, birth weight was significantly associated with several metals. On an IQR (25th to the 75th percentile) basis, estimated changes in birthweight were: for cobalt (82.5 g, IQR=6.05 µg/kg, p = 0.006), iron (-51.5 g, IQR = 171800 µg/kg, p = 0.030), manganese (-27.2 g, IQR=152.1 µg/kg, p = 0.017), lead (-72.7 g, IQR=16.55 µg/kg, p = 0.004) and rhodium (-1365.5 g, IQR = 0.33 µg/kg, p < 0.001). Finally, a generalized additive model showed significant nonlinear relationships between birth weight and concentrations of Co and Rh. CONCLUSIONS: Our comprehensive examination of placental metals illustrate many strong associations between lesser-studied metals and infant parameters. These data, in combination with our correlations of well-studied metals, illustrate a need to consider in utero exposure to a broad array of metals when considering fetal development.

Serum metallome in pregnant women and the relationship with congenital malformations of the central nervous system: a case-control study.

BACKGROUND: Congenital malformations of the central nervous system (CNS) consist of a wide range of birth defects of multifactorial origin. METHODS: Concentrations of 44 metals were determined by Inductively Coupled Plasma Mass Spectrometry in serum of 111 mothers in the second trimester of pregnancy who carried a malformed fetus and compared them with serum concentrations of the same metals in 90 mothers with a normally developed fetus at the same week of pregnancy. Data are reported as means ± standard deviations. RESULTS: We found a direct relationship between congenital defects of the CNS and maternal serum concentration of aluminum: it was statistically higher in women carrying a fetus with this class of malformation, compared both to mothers carrying a fetus with another class of malformation (6.45 ± 15.15 µg/L Vs 1.44 ± 4.21 µg/L, p < 0.0006) and to Controls (i.e. mothers carrying a normally-developed fetus) (6.45 ± 15.15 µg/L Vs 0.11 ± 0.51 µg/L, p < 0.0006). Moreover, Aluminum abundances were below the limit of detection in the majority of control samples. CONCLUSION: CAluminum may play a role in the onset of central nervous system malformations, although the exact Aluminum species and related specific type of malformation needs further elucidation.

Alterations in the properties of sperm protamine-like II protein after exposure of Mytilus galloprovincialis (Lamarck 1819) to sub-toxic doses of cadmium.

Protamine-like proteins (PL-II, PL-III and PL-IV) represent the major basic nuclear component of Mytilus galloprovincialis L sperm chromatin. The present study investigates the effects induced on the properties of PL-II protein after exposure of Mytilus galloprovincialis L for 24 h to 1.5 and 5 µM CdCl2. We found cadmium accumulation in protamine-like proteins with a linear grow up with the exposition dose. In particular, after 5 µM CdCl2 mussels exposure, the mobility of PL-II band changed in SDS-PAGE, suggesting structural rearrangement in presence of cadmium. Structural analysis using fluorescent probes, indicated that at 5 µM CdCl2 the complete conformational change of PL-II protein was reached. In the same condition of mussels exposure of 5 µM CdCl2, PL-II protein changed its DNA binding mode, which determined a closer DNA binding, because higher amount of NaCl were required for PL-II protein release by sperm nuclei. These results supported the hypothesis that mussel exposure to this CdCl2 dose, although lower to toxic ones, affects the properties of this protein and as a consequence chromatin organization of spermatozoa that is essential for the success of fertilization.

Metabolomic Signature of Endometrial Cancer.

Endometrial cancer (EC) is the most common cancer of the female reproductive tract in developed countries. At the moment, no effective screening system is available. Here, we evaluate the diagnostic performance of a serum metabolomic signature. Two enrollments were carried out, one consisting of 168 subjects: 88 with EC and 80 healthy women, was used for building the classification models. The second (used to establish the performance of the classification algorithm) was consisted of 120 subjects: 30 with EC, 30 with ovarian cancer, 10 with benign endometrial disease, and 50 healthy controls. Two ensemble models were built, one with all EC versus controls (Model I) and one in which EC patients were aggregated according to their histotype (Model II). Serum metabolomic analysis was conducted via gas chromatography-mass spectrometry, while classification was done by an ensemble learning machine. Accuracy ranged from 62% to 99% for the Model I and from 67% to 100% for the Model II. Ensemble model showed an accuracy of 100% both for Model I and II. The most important metabolites in class separation were lactic acid, progesterone, homocysteine, 3-hydroxybutyrate, linoleic acid, stearic acid, myristic acid, threonine, and valine. The serum metabolomics signature of endometrial cancer patients is peculiar because it differs from that of healthy controls and from that of benign endometrial disease and from other gynecological cancers (such as ovarian cancer).

Comparative assessment of the quality of commercial black and green tea using microbiology analyses.

BACKGROUND: Drinking tea constitutes a tradition which is deeply rooted in the culture of several countries. Moreover, in recent years, tea consumption is growing all over the world. Improper herbal tea storage (long periods, humid environments) represents a relevant health hazard for consumers because of the growth of bacteria and molds. RESULTS: This study analyzed 32 samples of commercially available black and green teas - purchased from southern Italy markets and online-shops - and the monitoring of microbiological quality of the tea bag content was performed. Evaluations were conducted with the aim of characterizing pathogens indicated by the European and American guidelines (total bacterial count, fungi and Escherichia coli) and on the research of Pseudomonas spp. and Clostridium perfringens. The presence of ochratoxin A in tea matrix-leaves and infusions was further assessed, using a validated and accredited HPLC-FLD method. Microbial loads, for over 80% samples, ranged from 1.0 × 102 to 2.8 × 105 CFU/g tea: most of identified microorganisms were classified as Bacillaceae. The utilization of rapid detection and identification methods (PCR and sequencing), allowed the characterization of strains of Pseudomonas psychrotolerans, Staphylococcus warneri, Pantoea gaviniae and the isolation of one strain of Clostridium perfringens, whose ability to produce toxins can result in harmful outcomes for consumers. Fungi were isolated from 70% samples: the most prevalent molds were Aspergillus niger strains, followed by Aspergillus tubingensis. Ochratoxin A was detected in 22 of 32 tea solid samples investigated: concentrations resulted over the indicated limits for food products for 50% samples. CONCLUSIONS: Results obtained demonstrated the need to develop targeted regulations for the safety of herbal teas.

A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more accurate and less operator-dependent screening method. OBJECTIVES: To perform a characterization of maternal serum in order to build a metabolomic fingerprint resulting from congenital anomalies of the central nervous system. METHODS: This is a case-control pilot study. Metabolomic profiles were obtained from serum of 168 mothers (98 controls and 70 cases), using gas chromatography coupled to mass spectrometry. Nine machine learning and classification models were built and optimized. An ensemble model was built based on results from the individual models. All samples were randomly divided into two groups. One was used as training set, the other one for diagnostic performance assessment. RESULTS: Ensemble machine learning model correctly classified all cases and controls. Propanoic, lactic, gluconic, benzoic, oxalic, 2-hydroxy-3-methylbutyric, acetic, lauric, myristic and stearic acid and myo-inositol and mannose were selected as the most relevant metabolites in class separation. CONCLUSION: The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal central nervous system anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is therefore a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the details of the most relevant metabolites and their respective biochemical pathways allow better understanding of the overall pathophysiology of affected pregnancies.

Placental tissue metabolome analysis by GC-MS: Oven-drying is a viable sample preparation method.

Analysis of the human placenta metabolome has great potential to advance the understanding of complicated pregnancies and deleterious fetal outcomes in remote populations, but samples preparation can present unique challenges. Herein, we introduce oven-drying as a simple and widely available method of sample preparation that will facilitate investigations of the placental metabolome from remote and under-studied populations. Placentae from complicated and uncomplicated pregnancies were prepared in three ways (oven-dried at 60 °C, fresh, lyophilized) for metabolome analysis via gas chromatography-mass spectrometry (GC-MS). Multiple computer models (e.g. PLS-DA, ANN) were employed to classify and determine if there was a difference in placentae metabolome and a group of metabolites with high variable importance in projection scores across the three preparations and by complicated vs. control groups. The analyses used herein were shown to be thorough and sensitive. Indeed, significant differences were detected in metabolomes of complicated vs. uncomplicated pregnancies; however, there were no statistical differences in the metabolome of placentae prepared by oven-drying vs. lyophilization vs. fresh placentae. Oven-drying is a viable sample preparation method for placentae intended for use in metabolite analysis via GC-MS. These results open many possibilities for researching metabolome patterns associated with fetal outcomes in remote and resource-poor communities worldwide.

The sexuological impact of hormonal contraceptives based on their route of administration.

Evidence on the effects of hormonal contraceptives on female sexuality is conflicting. We enrolled 556 women, divided into six groups: two composed of subjects using a combined hormonal contraceptive (COC) containing 0.020 ("COC20") and 0.030 ("COC30") mg of ethynyl estradiol (EE), "natural", using COC containing 1.5 mg of estradiol (E2), "ring", using a vaginal ring releasing each day 0.015 mg of EE + 0.120 of etonogestrel, "subcutaneous", using a progestin only subcutaneous contraceptive implant releasing etonogestrel and "controls", using no hormonal contraceptive methods. The subjects were required to answer to the McCoy female sexuality questionnaire and were subjected to a blood test for hormonal evaluation. An ultrasound evaluation of the dorsal clitoral artery was also performed. The higher McCoy sexological value were recorded in the subdermal group; significant differences were recorded among the groups in terms of hormone distribution, with the higher levels of androstenedione in subdermal and control groups. The ultrasound evaluation of dorsal clitoral artery shows a significative correlation between pulsatility and resistance indices and orgasm parameters of McCoy questionnaire. The recorded difference in the sexual and hormonal parameters among the studied hormonal contraceptives may guide toward the personalization of contraceptive choice.