Assessing the Clinical Efficacy of a Virtual Reality Tool for the Treatment of Obesity: Randomized Controlled Trial.

BACKGROUND: Virtual reality (VR) interventions, based on cognitive behavioral therapy principles, have been proven effective as complementary tools in managing obesity and have been associated with promoting healthy behaviors and addressing body image concerns. However, they have not fully addressed certain underlying causes of obesity, such as a lack of motivation to change, low self-efficacy, and the impact of weight stigma interiorization, which often impede treatment adherence and long-term lifestyle habit changes. To tackle these concerns, this study introduces the VR self-counseling paradigm, which incorporates embodiment and body-swapping techniques, along with motivational strategies, to help people living with obesity effectively address some of the root causes of their condition. OBJECTIVE: This study aims to assess the clinical efficacy of ConVRself (Virtual Reality self-talk), a VR platform that allows participants to engage in motivational self-conversations. METHODS: A randomized controlled trial was conducted with 68 participants from the bariatric surgery waiting list from the obesity unit of the Vall d'Hebron University Hospital in Barcelona, Spain. Participants were assigned to 1 of 3 groups: a control group (CG), which only received treatment as usual from the obesity unit; experimental group 1 (EG1), which, after intensive motivational interviewing training, engaged in 4 sessions of VR-based self-conversations with ConVRself, and underwent embodiment and body-swapping techniques; and experimental group 2 (EG2), which engaged in 4 VR-based sessions led by a virtual counselor with a prerecorded discourse, and only underwent the embodiment technique. In the case of both EG1 and EG2, the VR interventions were assisted by a clinical researcher. Readiness to change habits, eating habits, and psychological variables, as well as adherence and satisfaction with ConVRself were measured at baseline, after the intervention, 1 week after the intervention, and 4 weeks after the intervention. RESULTS: Regarding the primary outcomes, EG1 (24/68, 35%) and EG2 (22/68, 32%) showed significant improvements in confidence to lose weight compared to the CG (22/68, 32%) at all assessment points (ß=-.16; P=.02). Similarly, EG1 demonstrated a significant increase after the intervention in readiness to exercise more compared to the CG (ß=-.17; P=.03). Regarding the secondary outcomes, EG1 participants showed a significant reduction in uncontrolled eating (ß=.71; P=.01) and emotional eating (ß=.29; P=.03) compared to the CG participants, as well as in their anxiety levels compared to EG2 and CG participants (ß=.65; P=.01). In addition, participants from the experimental groups reported high adherence and satisfaction with the VR platform (EG1: mean 59.82, SD 4.00; EG2: mean 58.43, SD 5.22; d=0.30, 95% CI -0.30 to 0.89). CONCLUSIONS: This study revealed that using VR self-conversations, based on motivational interviewing principles, may have benefits in helping people with obesity to enhance their readiness to change habits and self-efficacy, as well as reduce dysfunctional eating behaviors and anxiety. TRIAL REGISTRATION: ClinicalTrials.gov NCT05094557; https://www.clinicaltrials.gov/study/NCT05094557.

Brain N-Glycosylation and Lipidomic Profile Changes Induced by a High-Fat Diet in Dyslipidemic Hamsters.

The consumption of diets rich in saturated fats is known to be associated with higher mortality. The adoption of healthy habits, for instance adhering to a Mediterranean diet, has proved to exert a preventive effect towards cardiovascular diseases and dyslipidemia. Little is known about how a suboptimal diet can affect brain function, structure, and the mechanisms involved. The aims of this study were to examine how a high-fat diet can alter the brain N-glycan and lipid profile in male Golden Syrian hamsters and to evaluate the potential of a Mediterranean-like diet to reverse this situation. During twelve weeks, hamsters were fed a normal fat diet (CTRL group), a high-fat diet (HFD group), and a high-fat diet followed by a Mediterranean-like diet (MED group). Out of seventy-two identified N-glycans, fourteen were significant (p < 0.05) between HFD and CTRL groups, nine between MED and CTRL groups, and one between MED and HFD groups. Moreover, forty-nine lipids were altered between HFD and CTRL groups, seven between MED and CTRL groups, and five between MED and HFD groups. Our results suggest that brain N-glycan composition in high-fat diet-fed hamsters can produce events comparable to those found in some neurodegenerative diseases, and may promote brain ageing.

Optimization of a GC-MS Injection-Port Derivatization Methodology to Enhance Metabolomics Analysis Throughput in Biological Samples.

Advances in metabolomics analysis and data treatment increase the knowledge of complex biological systems. One of the most used methodologies is gas chromatography-mass spectrometry (GC-MS) due to its robustness, high separation efficiency, and reliable peak identification through curated databases. However, methodologies are not standardized, and the derivatization steps in GC-MS can introduce experimental errors and take considerable time, exposing the samples to degradation. Here, we propose the injection-port derivatization (IPD) methodology to increase the throughput in plasma metabolomics analysis by GC-MS. The IPD method was evaluated and optimized for different families of metabolites (organic acids, amino acids, fatty acids, sugars, sugar phosphates, etc.) in terms of residence time, injection-port temperature, and sample/derivatization reagent ratio. Finally, the method's usefulness was validated in a study consisting of a cohort of obese patients with or without nonalcoholic steatohepatitis. Our results show a fast, reproducible, precise, and reliable method for the analysis of biological samples by GC-MS. Raw data are publicly available at MetaboLights with Study Identifier MTBLS5151.

Early antiretroviral therapy initiation effect on metabolic profile in vertically HIV-1-infected children.

BACKGROUND: Early combined antiretroviral treatment (cART) in perinatally acquired HIV-1 children has been associated with a rapid viral suppression, small HIV-1 reservoir size and reduced mortality and morbidity. Immunometabolism has emerged as an important field in HIV-1 infection offering both relevant knowledge regarding immunopathogenesis and potential targets for therapies against HIV-1. OBJECTIVES: To characterize the proteomic, lipidomic and metabolomic profile of HIV-1-infected children depending on their age at cART initiation. PATIENTS AND METHODS: Plasma samples from perinatally HIV-1-infected children under suppressive cART who initiated an early cART (first 12 weeks after birth, EARLY, n = 10) and late cART (12-50 weeks after birth, LATE, n = 10) were analysed. Comparative plasma proteomics, lipidomics and metabolomics analyses were performed by nanoLC-Orbitrap, UHPLC-qTOF and GC-qTOF, respectively. RESULTS: Seven of the 188 proteins identified exhibited differences comparing EARLY and LATE groups of HIV-1-infected children. Despite no differences in the lipidomic (n = 115) and metabolomic (n = 81) profiles, strong correlations were found between proteins and lipid levels as well as metabolites, including glucidic components and amino acids, with clinical parameters. The ratio among different proteins showed high discriminatory power of EARLY and LATE groups. CONCLUSIONS: Protein signature show a different proinflammatory state associated with a late cART introduction. Its associations with lipid levels and the relationships found between metabolites and clinical parameters may potentially trigger premature non-AIDS events in this HIV-1 population, including atherosclerotic diseases and metabolic disorders. Antiretroviral treatment should be started as soon as possible in perinatally acquired HIV-1-infected children to prevent them from future long-life complications.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis.

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Gelsolin: a new biomarker of disease activity in SLE patients associated with HDL-c.

OBJECTIVES: To identify potential biomarkers of disease activity analysing the proteome of high-density lipoprotein (HDL) particles from SLE patients in clinical remission and when they develop a flare compared with a healthy control group. METHODS: Quantitative proteomic analyses of purified HDL were performed using Tandem Mass Tag isobaric tag-labelling and nanoLC-Orbitrap (nLC-MS/MS) from nine SLE patients in clinical remission when they developed a flare and from nine healthy controls (9-9-9). We verified the identified proteins by Western blot and ELISA in a cohort of 104 SLE women patients, 46 healthy women and 14 SLE patients when a flare developed. RESULTS: We found 17 proteins with a significant fold-change (>1.1) compared with the control group. In lupus patients experiencing a flare compared with those in remission, we identified four proteins with a significant fold-change (C4, Indian Hedgehog protein, S100A8 and gelsolin). Plasma gelsolin (pGSN) levels were decreased in the 104 SLE patients (176.02(74.9) mcg/l) compared with the control group (217.13(86.7) mcg/l); P=0.005 and when they developed a clinical flare (104.84(41.7) mcg/l); P=0.002). pGSN levels were associated with HDL cholesterol levels (r = 0.316, P<0.001). Antimalarial treated patients showed significant higher levels of pGSN (214.56(88.94) mcg/l regarding 170.35(66.36) mcg/l); P = 0.017. CONCLUSION: Decreased pGSN are associated with clinical disease activity in SLE patients. Antimalarial treatment and HDL cholesterol are associated with higher levels of pGSN.

Proteomic Profile Associated With Loss of Spontaneous Human Immunodeficiency Virus Type 1 Elite Control.

BACKGROUND: Elite controllers (ECs) spontaneously control plasma human immunodeficiency virus type 1 (HIV-1) RNA without antiretroviral therapy. However, 25% lose virological control over time. The aim of this work was to study the proteomic profile that preceded this loss of virological control to identify potential biomarkers. METHODS: Plasma samples from ECs who spontaneously lost virological control (transient controllers [TCs]), at 2 years and 1 year before the loss of control, were compared with a control group of ECs who persistently maintained virological control during the same follow-up period (persistent controllers [PCs]). Comparative plasma shotgun proteomics was performed with tandem mass tag (TMT) isobaric tag labeling and nanoflow liquid chromatography coupled to Orbitrap mass spectrometry. RESULTS: Eighteen proteins exhibited differences comparing PC and preloss TC timepoints. These proteins were involved in proinflammatory mechanisms, and some of them play a role in HIV-1 replication and pathogenesis and interact with structural viral proteins. Coagulation factor XI, α-1-antichymotrypsin, ficolin-2, 14-3-3 protein, and galectin-3-binding protein were considered potential biomarkers. CONCLUSIONS: The proteomic signature associated with the spontaneous loss of virological control was characterized by higher levels of inflammation, transendothelial migration, and coagulation. Galectin-3 binding protein could be considered as potential biomarker for the prediction of virological progression and as therapeutic target in ECs.

Glutaminolysis and lipoproteins are key factors in late immune recovery in successfully treated HIV-infected patients.

The immunological, biochemical and molecular mechanisms associated with poor immune recovery are far from known, and metabolomic profiling offers additional value to traditional soluble markers. Here, we present novel and relevant data that could contribute to better understanding of the molecular mechanisms preceding a discordant response and HIV progression under suppressive combined antiretroviral therapy (cART). Integrated data from nuclear magnetic resonance (NMR)-based lipoprotein profiles, mass spectrometry (MS)-based metabolomics and soluble plasma biomarkers help to build prognostic and immunological progression tools that enable the differentiation of HIV-infected subjects based on their immune recovery status after 96 weeks of suppressive cART. The metabolomic signature of ART-naïve HIV subjects with a subsequent late immune recovery is the expression of pro-inflammatory molecules and glutaminolysis, which is likely related to elevate T-cell turnover in these patients. The knowledge about how these metabolic pathways are interconnected and regulated provides new targets for future therapeutic interventions not only in HIV infection but also in other metabolic disorders such as human cancers where glutaminolysis is the alternative pathway for energy production in tumor cells to meet their requirement of rapid proliferation.

Multi-omics approach to elucidate the gut microbiota activity: Metaproteomics and metagenomics connection.

Over the last few years, the application of high-throughput meta-omics methods has provided great progress in improving the knowledge of the gut ecosystem and linking its biodiversity to host health conditions, offering complementary support to classical microbiology. Gut microbiota plays a crucial role in relevant diseases such as obesity or cardiovascular disease (CVD), and its regulation is closely influenced by several factors, such as dietary composition. In fact, polyphenol-rich diets are the most palatable treatment to prevent hypertension associated with CVD, although the polyphenol-microbiota interactions have not been completely elucidated. For this reason, the aim of this study was to evaluate microbiota effect in obese rats supplemented by hesperidin, after being fed with cafeteria or standard diet, using a multi meta-omics approaches combining strategy of metagenomics and metaproteomics analysis. We reported that cafeteria diet induces obesity, resulting in changes in the microbiota composition, which are related to functional alterations at proteome level. In addition, hesperidin supplementation alters microbiota diversity and also proteins involved in important metabolic pathways. Overall, going deeper into strategies to integrate omics sciences is necessary to understand the complex relationships between the host, gut microbiota, and diet.

Proteomic Profile of Unstable Atheroma Plaque: Increased Neutrophil Defensin 1, Clusterin, and Apolipoprotein E Levels in Carotid Secretome.

Because of the clinical significance of carotid atherosclerosis, the search for novel biomarkers has become a priority. The aim of the present study was to compare the protein secretion profile of the carotid atherosclerotic plaque (CAP, n = 12) and nonatherosclerotic mammary artery (MA, n = 10) secretomes. We used a nontargeted proteomic approach that incorporated tandem immunoaffinity depletion, iTRAQ labeling, and nanoflow liquid chromatography coupled to high-resolution mass spectrometry. In total, 162 proteins were quantified, of which 25 showed statistically significant differences in secretome levels between carotid atherosclerotic plaque and nondiseased mammary artery. We found increased levels of neutrophil defensin 1, apolipoprotein E, clusterin, and zinc-alpha-2-glycoprotein in CAP secretomes. Results were validated by ELISA assays. Also, differentially secreted proteins are involved in pathways such as focal adhesion and leukocyte transendothelial migration. In conclusion, this study provides a subset of identified proteins that are differently expressed in secretomes of clinical significance.

Performance of zwitterionic hydrophilic interaction LC for the determination of iodinated X-ray contrast agents.

This study compares the separation performance of a group of iodinated X-ray contrast media on four different columns. The first three were two stationary phases (SPs) modified with C18 and a polar-embedded SP (polar amide group bonded to an alkyl chain), all of which worked under RP-LC mode. The fourth was a zwitterionic sulphoalkylbetaine SP, working under the hydrophilic interaction LC (HILIC) mode. After the optimisation of the different parameters, the zwitterionic column displayed the best separation, which also overcomes the problems encountered when these analytes were separated under RP-LC. Moreover, when HILIC is coupled to MS/MS, sensitivity is enhanced. However, when sewage samples were analysed by SPE followed by the optimal HILIC-MS/MS, the sensitivity of the method was affected due to the high matrix effect, which had to be solved by dilution of the extract. Finally, the method was preliminarily validated with sewage and the figures of merit were comparable to those of the SPE-RP-LC-MS/MS.

Fucosylated N-glycans as early biomarkers of COVID-19 severity.

Background: The pathological mechanisms of SARS-CoV-2 in humans remain unclear and the unpredictability of COVID-19 progression may be attributed to the absence of biomarkers that contribute to the prognosis of this disease. Therefore, the discovery of biomarkers is needed for reliable risk stratification and to identify patients who are more likely to progress to a critical stage. Methods: Aiming to identify new biomarkers we analysed N-glycan traits in plasma from 196 patients with COVID-19. Samples were classified into three groups according to their severity (mild, severe and critical) and obtained at diagnosis (baseline) and at 4 weeks of follow-up (postdiagnosis), to evaluate their behaviour through disease progression. N-glycans were released with PNGase F and labelled with Rapifluor-MS, followed by their analysis by LC-MS/MS. The Simglycan structural identification tool and Glycostore database were employed to predict the structure of glycans. Results: We determined that plasma from SARS-CoV-2-infected patients display different N-glycosylation profiles depending on the disease severity. Specifically, levels of fucosylation and galactosylation decreased with increasing severity and Fuc1Hex5HexNAc5 was identified as the most suitable biomarker to stratify patients at diagnosis and distinguish mild from critical outcomes. Conclusion: In this study we explored the global plasma glycosignature, reflecting the inflammatory state of the organs during the infectious disease. Our findings show the promising potential of glycans as biomarkers of COVID-19 severity.

Virtual self-conversation using motivational interviewing techniques to promote healthy eating and physical activity: A usability study.

Introduction: We aim to examine the usability of a Virtual Reality (VR) platform, called ConVRSelf, which has been designed to address the needs of People Living With Obesity (PLWO). Methods: Fourteen participants with a desire to eat healthier and exercise more (6 normal weight and 8 PLWO; Mean age = 41.86, SD = 13.89) were assigned to the experimental group (EG) or the control group (CG). EG participants, after being trained on motivational interviewing skills, engaged in a virtual self-conversation using embodiment and body swapping techniques, which aimed to normalize and resolve their ambivalence to change lifestyle habits. CG participants, embodied in their virtual bodies, participated in a pre-established discourse with a virtual counselor giving them psychoeducational advice about how to change lifestyle habits. A mixed-methods design was used, involving a semi-structured interview and self-report questionnaires, including readiness to change habits (Readiness Rulers), body ownership (Body Ownership Questionnaire, BOQ), and system usability (System Evaluation Questionnaire, SEQ). Thematic content analysis was carried out for qualitative data while statistical data analysis was carried out using SPSS 20.0. Results: Participants from both groups showed high readiness to change lifestyle (Readiness Rulers) before engaging with the virtual experiences, which was maintained at the same level after the interventions and their scores on the SEQ and BOQ were satisfactory. Regarding qualitative information obtained from the interviews, almost all participants found the VR experience to be novel, interesting, and enjoyable. A higher acceptability was observed among PLWO from the EG than normal weight participants from the same group, a promising finding for the ConVRSelf platform, which had been specifically designed to address the needs of PLWO. Conclusion: The ConVRSelf system is well-accepted by participants and is ready to be tested with PLWO in a clinical setting.

Machine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites.

In gas chromatography-mass spectrometry-based untargeted metabolomics, metabolites are identified by comparing mass spectra and chromatographic retention time with reference databases or standard materials. In that sense, machine learning has been used to predict the retention time of metabolites lacking reference data. However, the retention time prediction of trimethylsilyl derivatives of metabolites, typically analyzed in untargeted metabolomics using gas chromatography, has been poorly explored. Here, we provide a rationalized framework for machine learning-based retention time prediction of trimethylsilyl derivatives of metabolites in gas chromatography. We compared different machine learning paradigms, in addition to exploring the influence of the computational molecular structure representation to train the prediction models: fingerprint class and fingerprint calculation software. Our study challenged predicted retention time when using chemical ionization and electron impact ionization sources in simulated and real cases, demonstrating a good correct identity ranking capability by machine learning, despite observing a limited false identity filtering power in cases where a spectrum or a monoisotopic mass match to multiple candidates. Specifically, machine learning prediction yielded median absolute and relative retention index (relative retention time) errors of 37.1 retention index units and 2%, respectively. In addition, fingerprint class and fingerprint calculation software, as well as the molecular structural similarity between the training and test or real case sets, showed to be critical modulators of the prediction performance. Finally, we leveraged the structural similarity between the training and test or real case set to determine the probability that the prediction error is below a specific threshold. Overall, our study demonstrates that predicted retention time can provide insights into the true structure of unknown metabolites by ranking from the most to the least plausible molecular identity, and sets the guidelines to assess the confidence in metabolite identification using predicted retention time data.

Red-Fleshed Apples Rich in Anthocyanins and White-Fleshed Apples Modulate the Aorta and Heart Proteome in Hypercholesterolaemic Rats: The AppleCOR Study.

The impact of a red-fleshed apple (RFA) rich in anthocyanins (ACNs), a white-fleshed apple (WFA) without ACNs, and an extract infusion from Aronia fruit (AI) equivalent in dose of cyanidin-3-O-galactoside (main ACN) as RFA was determined by the proteome profile of aorta and heart as key cardiovascular tissues. Hypercholesterolaemic Wistar rats were separated into six groups (n = 6/group; three males and three females) and the proteomic profiles were analyzed using nanoliquid chromatography coupled to mass spectrometry. No adverse events were reported and all products were well tolerated. RFA downregulated C1QB and CFP in aorta and CRP in heart. WFA downregulated C1QB and CFP in aorta and C9 and C3 in aorta and heart, among other proteins. AI downregulated PRKACA, IQGAP1, and HSP90AB1 related to cellular signaling. Thus, both apples showed an anti-inflammatory effect through the complement system, while RFA reduced CRP. Regardless of the ACN content, an apple matrix effect was observed that involved different bioactive components, and inflammatory proteins were reduced.

Hesperidin Bioavailability Is Increased by the Presence of 2S-Diastereoisomer and Micronization-A Randomized, Crossover and Double-Blind Clinical Trial.

Hesperidin is a flavanone abundantly found in citrus fruits for which health beneficial effects have been reported. However, hesperidin shows a low bioavailability among individuals. The aim of this study was to evaluate the effects of the micronization process and 2R- and 2S-hesperidin diastereoisomers ratio on hesperidin bioavailability. In a first phase, thirty healthy individuals consumed 500 mL of orange juice with 345 mg of hesperidin, and the levels of hesperidin metabolites excreted in urine were determined. In the second phase, fifteen individuals with intermediate hesperidin metabolite levels excreted in urine were randomized in a crossover, postprandial and double-blind intervention study. Participants consumed 500 mg of the hesperidin-supplemented Hesperidin epimeric mixture (HEM), the micronized Hesperidin epimeric mixture (MHEM) and micronized 2S-Hesperidin (M2SH) in each study visit with 1 week of washout. Hesperidin metabolites and catabolites were determined in blood and urine obtained at different timepoints over a 24 h period. The bioavailability-relative urinary hesperidin excretion (% of hesperidin ingested)-of M2SH (70 ± 14%) formed mainly by 2S-diastereoisomer was significantly higher than the bioavailability of the MHEM (55 ± 15%) and HEM (43 ± 8.0%), which consisted of a mixture of both hesperidin diastereoisomers. Relative urinary excretion of hesperidin metabolites for MHEM (9.2 ± 1.6%) was significantly higher compared to the HEM (5.2 ± 0.81%) and M2SH (3.6 ± 1.0%). In conclusion, the bioavailability of 2S-hesperidin extract was higher compared to the standard mixture of 2S-/2R-hesperidin extract due to a greater formation of hesperidin catabolites. Furthermore, the micronization process increased hesperidin bioavailability.

The Interplay between Pathophysiological Pathways in Early-Onset Severe Preeclampsia Unveiled by Metabolomics.

INTRODUCTION: Preeclampsia is a multi-system disorder unique to pregnancy responsible for a great part of maternal and perinatal morbidity and mortality. The precise pathogenesis of this complex disorder is still unrevealed. METHODS: We examined the pathophysiological pathways involved in early-onset preeclampsia, a specific subgroup representing its most severe presentation, using LC-MS/MS metabolomic analysis based on multi-level extraction of lipids and small metabolites from maternal blood samples, collected at the time of diagnosis from 14 preeclamptic and six matched healthy pregnancies. Statistical analysis comprised multivariate and univariate approaches with the application of over representation analysis to identify differential pathways. RESULTS: A clear difference between preeclamptic and control pregnancies was observed in principal component analysis. Supervised multivariate analysis using orthogonal partial least square discriminant analysis provided a robust model with goodness of fit (R2X = 0.91, p = 0.002) and predictive ability (Q2Y = 0.72, p < 0.001). Finally, univariate analysis followed by 5% false discovery rate correction indicated 82 metabolites significantly altered, corresponding to six overrepresented pathways: (1) aminoacyl-tRNA biosynthesis; (2) arginine biosynthesis; (3) alanine, aspartate and glutamate metabolism; (4) D-glutamine and D-glutamate metabolism; (5) arginine and proline metabolism; and (6) histidine metabolism. CONCLUSION: Metabolomic analysis focusing specifically on the early-onset severe form of preeclampsia reveals the interplay between pathophysiological pathways involved in this form. Future studies are required to explore new therapeutic approaches targeting these altered metabolic pathways in early-onset preeclampsia.

Microbial bile salt hydrolase activity influences gene expression profiles and gastrointestinal maturation in infant mice.

The mechanisms by which early microbial colonizers of the neonate influence gut development are poorly understood. Bacterial bile salt hydrolase (BSH) acts as a putative colonization factor that influences bile acid signatures and microbe-host signaling pathways and we considered whether this activity can influence infant gut development. In silico analysis of the human neonatal gut metagenome confirmed that BSH enzyme sequences are present as early as one day postpartum. Gastrointestinal delivery of cloned BSH to immature gnotobiotic mice accelerated shortening of the colon and regularized gene expression profiles, with monocolonised mice more closely resembling conventionally raised animals. In situ expression of BSH decreased markers of cell proliferation (Ki67, Hes2 and Ascl2) and strongly increased expression of ALPI, a marker of cell differentiation and barrier function. These data suggest an evolutionary paradigm whereby microbial BSH activity potentially influences bacterial colonization and in-turn benefits host gastrointestinal maturation.

Metabolites Secreted by Bovine Embryos In Vitro Predict Pregnancies That the Recipient Plasma Metabolome Cannot, and Vice Versa.

This work describes the use of mass spectrometry-based metabolomics as a non-invasive approach to accurately predict birth prior to embryo transfer (ET) starting from embryo culture media and plasma recipient. Metabolomics was used here as a predictive platform. Day-6 in vitro produced embryos developed singly in modified synthetic oviduct fluid culture medium (CM) drops for 24 h were vitrified as Day-7 blastocysts and transferred to recipients. Day-0 and Day-7 recipient plasma (N = 36 × 2) and CM (N = 36) were analyzed by gas chromatography coupled to the quadrupole time of flight mass spectrometry (GC-qTOF). Metabolites quantified in CM and plasma were analyzed as a function to predict pregnancy at Day-40, Day-62, and birth (univariate and multivariate statistics). Subsequently, a Boolean matrix (F1 score) was constructed with metabolite pairs (one from the embryo, and one from the recipient) to combine the predictive power of embryos and recipients. Validation was performed in independent cohorts of ETs analyzed. Embryos that did not reach birth released more stearic acid, capric acid, palmitic acid, and glyceryl monostearate in CM (i.e., (p < 0.05, FDR < 0.05, Receiver Operator Characteristic-area under curve (ROC-AUC) > 0.669)). Within Holstein recipients, hydrocinnamic acid, alanine, and lysine predicted birth (ROC-AUC > 0.778). Asturiana de los Valles recipients that reached birth showed lower concentrations of 6-methyl-5-hepten-2-one, stearic acid, palmitic acid, and hippuric acid (ROC-AUC > 0.832). Embryonal capric acid and glyceryl-monostearate formed F1 scores generally >0.900, with metabolites found both to differ (e.g., hippuric acid, hydrocinnamic acid) or not (e.g., heptadecanoic acid, citric acid) with pregnancy in plasmas, as hypothesized. Efficient lipid metabolism in the embryo and the recipient can allow pregnancy to proceed. Changes in phenolics from plasma suggest that microbiota and liver metabolism influence the pregnancy establishment in cattle.

Analysis of oxylipins to differentiate between organic and conventional UHT milks.

Nowadays, there is a strong interest in analytical approaches for assessing organic farming practices. Here, we propose that oxylipins, a group of oxidised metabolites derived from various polyunsaturated fatty acids, could be promising biomarkers for organic milk assessment because their biosynthesis is modulated by both precursor fatty acid availability and physiological or pathological status. Thus, we determined 31 fatty acids, 53 triacylglycerols and 37 oxylipins in one hundred commercial UHT milks by chromatographic methods coupled to mass spectrometry. Of these, 52 milks were conventional (34 whole milk, 11 semi-skimmed milk and 7 skimmed milk) and 48 were organic (31 whole milk, 11 semi-skimmed milk and 6 skimmed milk). Several oxylipins (8-HEPE, 5-HEPE, 11-HEPE, 9-HEPE, 18-HEPE, 9-HOTrE, 13-HOTrE, 12,13-DiHODE and 15,16-DiHODE) could distinguish between organic and conventional milks. Within these oxylipins, arachidonic and linoleic acid derived do not correlate with their fatty acid precursors; therefore these oxylipins could be promising as not only diet-dependent biomarkers for organic milk assessment.