Search

Abstract Background Crohn’s disease (CD) is characterized by chronic intestinal inflammation. Diet is a key modifiable factor influencing the gut microbiome (GM) and a risk factor for CD. However, the impact of diet modulation on GM function in CD patients is understudied. Herein, we evaluated the effect of a high-fiber, low-fat diet (the Mi-IBD diet) on GM function in CD patients. All participants were instructed to follow the Mi-IBD diet for 8 weeks. One group of CD patients received one-time diet counseling only (Gr1); catered food was supplied for the other three groups, including CD patients (Gr2) and dyads of CD patients and healthy household controls (HHCs) residing within the same household (Gr3-HHC dyads). Stool samples were collected at baseline, week 8, and week 36, and analyzed by liquid chromatography-tandem mass spectrometry. Results At baseline, the metaproteomic profiles of CD patients and HHCs differed. The Mi-IBD diet significantly increased carbohydrate and iron transport and metabolism. The predicted microbial composition underlying the metaproteomic changes differed between patients with ileal only disease (ICD) or colonic involvement: ICD was characterized by decreased Faecalibacterium abundance. Even on the Mi-IBD diet, the CD patient metaproteome displayed significant underrepresentation of carbohydrate and purine/pyrimidine synthesis pathways compared to that of HHCs. Human immune-related proteins were upregulated in CD patients compared to HHCs. Conclusions The Mi-IBD diet changed the microbial function of CD patients and enhanced carbohydrate metabolism. Our metaproteomic results highlight functional differences in the microbiome according to disease location. Notably, our dietary intervention yielded the most benefit for CD patients with colonic involvement compared to ileal-only disease. Video Abstract

Abstract Background Thoracic surgery is a high-risk surgery especially for the risk of postoperative pulmonary complications. Postoperative residual paralysis has been shown to be a risk factor for pulmonary complications. Nevertheless, there are few data in the literature concerning the use of neuromuscular blocking agent antagonists in patients undergoing lung surgery. Methods Seventy patients were randomized in three Italian centers to receive sugammadex or neostigmine at the end of thoracic surgery according to the depth of the residual neuromuscular block. The primary outcome was the time from reversal administration to a train-of-four ratio (TOFR) of 0.9. Secondary outcomes were the time to TOFR of 1.0, to extubation, to postanesthesia unit (PACU) discharge, postoperative complications until 30 days after surgery, and length of hospital stay. Results Median time to recovery to a TOFR of 0.9 was significantly shorter in the sugammadex group compared to the neostigmine one (88 vs. 278 s — P

Instruments measuring aerosol light absorption, such as the Aethalometer and the Multi-Wavelength Absorbance Analyzer (MWAA), have been extensively used to characterize optical absorption of atmospheric particulate matter. Data retrieved with such instruments can be analysed with mathematical models to apportion different aerosol sources (Aethalometer model) and components (MWAA model). In this work we present an upgrade to the MWAA optical apportionment model. In addition to the apportionment of the absorption coefficient babs in its components (black carbon and brown carbon) and sources (fossil fuels and wood burning), the extended model allows for the retrieval of the absorption Ångström exponent of each component and source, thereby avoiding initial assumptions regarding these parameters. We also present a new open-source software toolkit, the MWAA model toolkit (MWAA_MT), written in both Python and R, that performs the entire apportionment procedure.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. Investigations of gut microbiota (GM) play an important role in deciphering disease severity and symptoms. Overall, we stratified 70 ASD patients by neuropsychological assessment, based on Calibrated Severity Scores (CSSs) of the Autism Diagnostic Observation Schedule-Second edition (ADOS-2), Child Behavior Checklist (CBCL) and intelligent quotient/developmental quotient (IQ/DQ) parameters. Hence, metataxonomy and PICRUSt-based KEGG predictions of fecal GM were assessed for each clinical subset. Here, 60% of ASD patients showed mild to moderate autism, while the remaining 40% showed severe symptoms; 23% showed no clinical symptoms, 21% had a risk of behavior problems and 56% had clinical symptoms based on the CBCL, which assesses internalizing problems; further, 52% had no clinical symptoms, 21% showed risk, and 26% had clinical symptoms classified by CBCL externalizing problems. Considering the total CBCL index, 34% showed no clinical symptoms, 13% showed risk, and 52% had clinical symptoms. Here, 70% of ASD patients showed cognitive impairment/developmental delay (CI/DD). The GM of ASDs with severe autism was characterized by an increase in Veillonella, a decrease in Monoglobus pectinilyticus and a higher microbial dysbiosis index (MDI) when compared to mild-moderate ASDs. Patients at risk for behavior problems and showing clinical symptoms were characterized by a GM with an increase of Clostridium, Eggerthella, Blautia, Intestinibacter, Coprococcus, Ruminococcus, Onthenecus and Bariatricus, respectively. Peptidoglycan biosynthesis and biofilm formation KEGGs characterized patients with clinical symptoms, while potential microbiota-activated PPAR-γ-signaling was seen in CI/DD patients. This evidence derived from GM profiling may be used to further improve ASD understanding, leasing to a better comprehension of the neurological phenotype.

Clostridioides difficile infection (CDI) is generally treated with vancomycin, metronidazole or fidaxomicin, although fecal microbiota transplantation (FMT) represents a promising therapeutic option for antibiotic-resistant recurrent C. difficile infections (rCDIs) in adults. In pediatric cystic fibrosis (CF) patients, CDIs are generally asymptomatic and respond to treatment. Here, we present the case of an 8-year-old female, initially diagnosed as “CFTR-related metabolic syndrome/cystic fibrosis screen positive, inconclusive diagnosis” (CMRS/CFSPID), who then progressed to CF at 12 months. In the absence of CF-related symptoms, she presented multiple and disabling episodes of bloody diarrhoea with positive tests for C. difficile antigen and A/B toxin. After conventional treatments failed and several CDI relapses, FMT was proposed. Donor screening and GM donor–receiver matching identified her mother as a donor. Metataxonomy and targeted metabolomics provided, through a pre- and post-FMT time course, gut microbiota (GM) profiling to assess GM engraftment. At first, the GM map revealed severe dysbiosis, with a prevalence of Bacteroidetes and Proteobacteria (i.e., Klebsiella spp., Escherichia coli), a reduction in Firmicutes, a GM nearly entirely composed of Enterococcaceae (i.e., Enterococcus) and an almost complete depletion of Verrucomicrobia and Actinobacteria, mostly represented by Veillonella dispar. Post FMT, an increment in Bifidobacterium spp. and Collinsella spp. with a decrease in V. dispar restored intestinal eubiosis. Consistently, four weeks after FMT treatment, the child’s gut symptoms cleared, without CDI recurrence.

BackgroundUlcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD) that affects the large intestine with superficial mucosal inflammation. A dysbiotic gut microbial profile has been associated with UC. Our study aimed to characterize the UC gut bacterial, fungal, and metabolic fingerprints by omic approaches.MethodsThe 16S rRNA- and ITS2-based metataxonomics and gas chromatography–mass spectrometry/solid phase microextraction (GC–MS/SPME) metabolomic analysis were performed on stool samples of 53 UC patients and 37 healthy subjects (CTRL). Univariate and multivariate approaches were applied to separated and integrated omic data, to define microbiota, mycobiota, and metabolic signatures in UC. The interaction between gut bacteria and fungi was investigated by network analysis.ResultsIn the UC cohort, we reported the increase of Streptococcus, Bifidobacterium, Enterobacteriaceae, TM7-3, Granulicatella, Peptostreptococcus, Lactobacillus, Veillonella, Enterococcus, Peptoniphilus, Gemellaceae, and phenylethyl alcohol; and we also reported the decrease of Akkermansia; Ruminococcaceae; Ruminococcus; Gemmiger; Methanobrevibacter; Oscillospira; Coprococus; Christensenellaceae; Clavispora; Vishniacozyma; Quambalaria; hexadecane; cyclopentadecane; 5-hepten-2-ol, 6 methyl; 3-carene; caryophyllene; p-Cresol; 2-butenal; indole, 3-methyl-; 6-methyl-3,5-heptadiene-2-one; 5-octadecene; and 5-hepten-2-one, 6 methyl. The integration of the multi-omic data confirmed the presence of a distinctive bacterial, fungal, and metabolic fingerprint in UC gut microbiota. Moreover, the network analysis highlighted bacterial and fungal synergistic and/or divergent interkingdom interactions.ConclusionIn this study, we identified intestinal bacterial, fungal, and metabolic UC-associated biomarkers. Furthermore, evidence on the relationships between bacterial and fungal ecosystems provides a comprehensive perspective on intestinal dysbiosis and ecological interactions between microorganisms in the framework of UC.

Abstract Williams–Beuren syndrome (WBS) is a rare genetic neurodevelopmental disorder with multi-systemic manifestations. The evidence that most subjects with WBS face gastrointestinal (GI) comorbidities, have prompted us to carry out a metaproteomic investigation of their gut microbiota (GM) profile compared to age-matched healthy subjects (CTRLs). Metaproteomic analysis was carried out on fecal samples collected from 41 individuals with WBS, and compared with samples from 45 CTRLs. Stool were extracted for high yield in bacterial protein group (PG) content, trypsin-digested and analysed by nanoLiquid Chromatography-Mass Spectrometry. Label free quantification, taxonomic assignment by the lowest common ancestor (LCA) algorithm and functional annotations by COG and KEGG databases were performed. Data were statistically interpreted by multivariate and univariate analyses. A WBS GM functional dissimilarity respect to CTRLs, regardless age distribution, was reported. The alterations in function of WBSs GM was primarily based on bacterial pathways linked to carbohydrate transport and metabolism and energy production. Influence of diet, obesity, and GI symptoms was assessed, highlighting changes in GM biochemical patterns, according to WBS subsets’ stratification. The LCA-derived ecology unveiled WBS-related functionally active bacterial signatures: Bacteroidetes related to over-expressed PGs, and Firmicutes, specifically the specie Faecalibacterium prausnitzii, linked to under-expressed PGs, suggesting a depletion of beneficial bacteria. These new evidences on WBS gut dysbiosis may offer novel targets for tailored interventions.

Biological particulate matter or bioaerosol are a subset of atmospheric aerosol. They influence climate, air quality, and health via several mechanisms which often are poorly understood. In particular, the quantitative study of possible relationship between bioaerosol viability and air quality or meteorological conditions is an open and relevant issue. The difficulty of retrieving such possible correlations by analyses of data collected during in-field campaigns can benefit of targeted experiments conducted in well-controlled conditions inside atmospheric simulation chambers (ASCs). ChAMBRe (Chamber for Aerosol Modelling and Bio-aerosol Research) is an ASC in Genoa (Italy) designed and built to perform experimental research on bioaerosol. In this article, we focus on bacteria viability. A multi-step protocol was developed and thoroughly tested to cultivate a suitable bacteria population (E. coli), nebulize and inject in a chamber of viable cells, expose and monitor the viability variation inside ChAMBRe, hold at selected conditions, and finally incubate and count the concentration of viable bacteria. The whole procedure showed an estimated lifetime of total (T) and viable (V) E. coli of about 153 and 32 min, respectively and a V : T lifetime ratio of 40±5 min when ChAMBRe is held in a reference baseline condition. The coefficient of variation of 13 % shows how sensitive the protocol is also to changes in viability when the bacteria are exposed to other (e.g. polluted) conditions. First results showing a viability reduction observed exposing the E. coli strain to NOx concentrations and solar irradiation are presented and discussed. The present results pave the way for systematic studies aimed at the definition of dose–effect relationship for several bacteria strains under different conditions of atmospheric pollutants.

The airborne transmission of bacterial pathogens poses a significant challenge to public health, especially with the emergence of antibiotic-resistant strains. This study investigated environmental factors influencing the survival of airborne bacteria, focusing on the effects of different carbon dioxide (CO2) and dust concentrations. The experiments were conducted in an atmospheric simulation chamber using the non-resistant wild-type E. coli K12 (JM109) and a multi-resistant variant (JM109-pEC958). Different CO2 (100 ppm, 800 ppm, 3000 ppm) and dust concentrations (250 µg m−3, 500 µg m−3, 2000 µg m−3) were tested to encompass a wide range of CO2 and dust levels. The results revealed that JM109-pEC958 exhibited greater resilience to high CO2 and dust concentrations compared to its non-resistant counterpart. At 3000 ppm CO2, the survival rate of JM109 was significantly reduced, while the survival rate of JM109-pEC958 remained unaffected. At the dust concentration of 250 µg m−3, JM109 exhibited significantly reduced survival, whereas JM109-pEC958 did not. When the dust concentration was increased to 500 and 2000 µg m−3, even the JM109-pEC958 experienced substantially reduced survival rates, which were still significantly higher than those of its non-resistant counterpart at these concentrations. These findings suggest that multi-resistant E. coli strains possess mechanisms enabling them to endure extreme environmental conditions better than non-resistant strains, potentially involving regulatory genes or efflux pumps. The study underscores the importance of understanding bacterial adaptation strategies to develop effective mitigation approaches against antibiotic-resistant bacteria in atmospheric environments. Overall, this study provides valuable insights into the interplay between environmental stressors and bacterial survival, serving as a foundational step towards elucidating the adaptation mechanisms of multi-resistant bacteria and informing strategies for combating antibiotic resistance in the atmosphere.

IntroductionThe gut microbiota (GM) play a significant role in the infectivity and severity of COVID-19 infection. However, the available literature primarily focuses on adult patients and it is known that the microbiota undergoes changes throughout the lifespan, with significant alterations occurring during infancy and subsequently stabilizing during adulthood. Moreover, children have exhibited milder symptoms of COVID-19 disease, which has been associated with the abundance of certain protective bacteria. Here, we examine the metaproteome of pediatric patients to uncover the biological mechanisms that underlie this protective effect of the GM.MethodsWe performed nanoliquid chromatography coupled with tandem mass spectrometry on a high resolution analytical platform, resulting in label free quantification of bacterial protein groups (PGs), along with functional annotations via COG and KEGG databases by MetaLab-MAG. Additionally, taxonomic assignment was possible through the use of the lowest common ancestor algorithm provided by Unipept software.ResultsA COVID-19 GM functional dissimilarity respect to healthy subjects was identified by univariate analysis. The alteration in COVID-19 GM function is primarily based on bacterial pathways that predominantly involve metabolic processes, such as those related to tryptophan, butanoate, fatty acid, and bile acid biosynthesis, as well as antibiotic resistance and virulence.DiscussionThese findings highlight the mechanisms by which the pediatric GM could contribute to protection against the more severe manifestations of the disease in children. Uncovering these mechanisms can, therefore, have important implications in the discovery of novel adjuvant therapies for severe COVID-19.

BackgroundAutism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata.MethodsFecal samples collected from children with ASD and neurotypical children were analyzed by gas-chromatography mass spectrometry coupled with solid phase microextraction (GC–MS/SPME) to determine volatile organic compounds (VOCs) associated with the metataxonomic approach by 16S rRNA gene sequencing. Multivariate and univariate statistical analyses assessed differential VOC profiles and relationships with ASD anamnestic and clinical features for biomarker discovery. Multiple web-based and machine learning (ML) models identified metabolic predictors of disease and network analyses correlated GM ecological and metabolic patterns.ResultsThe GM core volatilome for all ASD patients was characterized by a high concentration of 1-pentanol, 1-butanol, phenyl ethyl alcohol; benzeneacetaldehyde, octadecanal, tetradecanal; methyl isobutyl ketone, 2-hexanone, acetone; acetic, propanoic, 3-methyl-butanoic and 2-methyl-propanoic acids; indole and skatole; and o-cymene. Patients were stratified based on age, GI symptoms, and ASD severity symptoms. Disease risk prediction allowed us to associate butanoic acid with subjects older than 5 years, indole with the absence of GI symptoms and low disease severity, propanoic acid with the ASD risk group, and p-cymene with ASD symptoms, all based on the predictive CBCL-EXT scale. The HistGradientBoostingClassifier model classified ASD patients vs. CTRLs by an accuracy of 89%, based on methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, ethanol, butanoic acid, octadecane, acetic acid, skatole, and tetradecanal features. LogisticRegression models corroborated methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, skatole, and acetic acid as ASD predictors.ConclusionOur results will aid the development of advanced clinical decision support systems (CDSSs), assisted by ML models, for advanced ASD-personalized medicine, based on omics data integrated into electronic health/medical records. Furthermore, new ASD screening strategies based on GM-related predictors could be used to improve ASD risk assessment by uncovering novel ASD onset and risk predictors.

Ischemic stroke (IS) can be caused by perturbations of the gut–brain axis. An imbalance in the gut microbiota (GM), or dysbiosis, may be linked to several IS risk factors and can influence the brain through the production of different metabolites, such as short-chain fatty acids (SCFAs), indole and derivatives. This study examines ecological changes in the GM and its metabolic activities after stroke. Fecal samples of 10 IS patients were compared to 21 healthy controls (CTRLs). GM ecological profiles were generated via 16S rRNA taxonomy as functional profiles using metabolomics analysis performed with a gas chromatograph coupled to a mass spectrometer (GC-MS). Additionally fecal zonulin, a marker of gut permeability, was measured using an enzyme-linked immuno assay (ELISA). Data were analyzed using univariate and multivariate statistical analyses and correlated with clinical features and biochemical variables using correlation and nonparametric tests. Metabolomic analyses, carried out on a subject subgroup, revealed a high concentration of fecal metabolites, such as SCFAs, in the GM of IS patients, which was corroborated by the enrichment of SCFA-producing bacterial genera such as Bacteroides, Christensellaceae, Alistipes and Akkermansia. Conversely, indole and 3-methyl indole (skatole) decreased compared to a subset of six CTRLs. This study illustrates how IS might affect the gut microbial milieu and may suggest potential microbial and metabolic biomarkers of IS. Expanded populations of Akkermansia and enrichment of acetic acid could be considered potential disease phenotype signatures.

The performance of a mini inverted soot generator (MISG) has been investigated at ChAMBRe (Chamber for Aerosol Modelling and Bio-aerosol Research) by studying the properties of soot particles generated by ethylene and propane combustion. This work deepens and expands the existing characterization of the MISG, which also exploits an atmospheric simulation chamber (ASC). Different from previous works, MISG performance has been also tested at different fuel flows and higher global equivalence ratios. MISG exhausts were investigated after their injection inside the atmospheric simulation chamber, which is another novelty of this work. Starting from an extensive classification of combustion conditions and resulting flame shapes, the MISG exhaust was characterized in terms of concentration of emitted particles and gases, particle size distribution, and optical properties. Soot particles were also collected on quartz fibre filters and then analysed by optical and thermal–optical techniques to measure the spectral dependence of the absorption coefficient babs​​​​​​​ and their composition in terms of elemental carbon and organic carbon (EC and OC). Significant differences could be observed when the MISG was fuelled with ethylene and propane in terms of particle size. In particular, the production of super-micrometric aggregates was observed for ethylene combustion. With equal combustion conditions, ethylene produced a higher number concentration of particles and smaller mode diameters. Soot particles produced by propane combustion resulted in higher EC : TC (total carbon) ratios and they were more light absorbing than particles generated by ethylene combustion. Values of the mass absorption cross section (MAC) and of the Ångström absorption exponent (AAE) turned out to be compatible with the literature, even if there were some specific differences. The comprehensive characterization of the MISG soot particles is an important piece of information to design and perform experiments in atmospheric simulation chambers. Particles with well-known properties can be used, for example, to investigate the possible interactions between soot and other atmospheric pollutants, the effects of meteorological variables on soot properties, and the oxidative and toxicological potential of soot particles.

Vitamin D has been proven to be a strong stimulator of mechanisms associated with the elimination of pathogens. Because of its recognized effectiveness against viral infections, during SARS-CoV-2 infection, the effects of Vitamin D supplementation have been the object of debate. This study aims to contribute to this debate by the means of a qualitative phenomenological mathematical model in which the role of Vitamin D and its interactions with the innate immune system are explicitly considered. We show that Vitamin D influx and degradation can be considered as possible control parameters for the disease evaluation and recovery. By varying Vitamin D influx, three dynamical scenarios have been found with different modalities of recovery from the disease. Inside each scenario, Vitamin D degradation has been related to different degrees of severity in disease development. Interestingly, the emergence of hysteretic phenomenologies when Vitamin D influx is too low can be related to the onset of Long-COVID syndrome, confirming clinical evidence from recent studies on the topic.

Biological particulate matter (BioPM) is a poorly constrained, ubiquitous, and diverse subset of atmospheric aerosols. They influence climate, air quality, and health via many mechanisms, spurring renewed interest in constraining their emissions to elucidate their impacts. In order to build the framework required to assess the role of BioPM in these multidisciplinary areas, it is necessary to develop robust, high time-resolution detection methodologies so that BioPM emissions can be understood and characterized. In this study, we present ambient results from intensive monitoring at UK peri-urban and coastal ground sites using high time-resolution real-time bioaerosol spectrometers. We demonstrate the utility of a new dimensional reduction-driven BioPM classification scheme, where laboratory sample training data collected at the ChAMBRe facility were used to generate broad taxonomic class time series data of key species of interest. We show the general trends of these representative classes, spanning spring, early summer, and autumn periods between 2019 and 2021. Diurnal behaviors and meteorological relationships were investigated and contextualized; a key result arising from this study was the demonstration of rainfall-induced enhancement of nighttime Penicillium-like aerosol, where rainfall crucially only acts to enhance the quantity emitted without significantly influencing the early morning timing of peak spore liberation.

The interplay of bio-aerosol dispersion and impact, meteorology, and air quality is gaining increasing interest in the wide spectrum of atmospheric sciences. Experiments conducted inside confined artificial environments, such as atmospheric simulation chambers (ASCs), where atmospheric conditions and composition are controlled, can provide valuable information on bio-aerosol viability, dispersion, and impact. We focus here on the reproducible aerosolization and injection of viable microorganisms into an ASC, the first and crucial step of any experimental protocol to expose bio-aerosols to different atmospheric conditions. We compare the performance of three nebulizers specifically designed for bio-aerosol applications: the Collison nebulizer, the Blaustein Atomizing Modules (BLAM), and the Sparging Liquid Aerosol Generator (SLAG), all manufactured and commercialized by CH TECHNOLOGIES. The comparison refers to operating conditions and the concentration of viable bacteria at the nebulizer outlet, with the final goal being to measure the reproducibility of the nebulization procedures and assess their application in experiments inside ASCs. A typical bacterial test model, Escherichia coli (ATCC® 25922™), was selected for such characterization. Bacteria suspensions with a concentration around 108 CFU mL−1 were first aerosolized at different air pressures and collected by a liquid impinger to obtain a correlation curve between airflow and nebulized bacteria for each generator. Afterwards, bacteria were aerosolized inside the atmospheric simulation chamber ChAMBRe (Chamber for Aerosol Modelling and Bio-aerosol Research) to measure the reproducibility of the whole procedure. An overall reproducibility of 11 % (i.e., standard deviation of the results obtained with the three nebulizers) was obtained with each nebulizer through a set of baseline experiments.

Autism spectrum disorders (ASDs) is a multifactorial neurodevelopmental disorder. The communication between the gastrointestinal (GI) tract and the central nervous system seems driven by gut microbiota (GM). Herein, we provide GM profiling, considering GI functional symptoms, neurological impairment, and dietary habits. Forty-one and 35 fecal samples collected from ASD and neurotypical children (CTRLs), respectively, (age range, 3–15 years) were analyzed by 16S targeted-metagenomics (the V3–V4 region) and inflammation and permeability markers (i.e., sIgA, zonulin lysozyme), and then correlated with subjects’ metadata. Our ASD cohort was characterized as follows: 30/41 (73%) with GI functional symptoms; 24/41 (58%) picky eaters (PEs), with one or more dietary needs, including 10/41 (24%) with food selectivity (FS); 36/41 (88%) presenting high and medium autism severity symptoms (HMASSs). Among the cohort with GI symptoms, 28/30 (93%) showed HMASSs, 17/30 (57%) were picky eaters and only 8/30 (27%) with food selectivity. The remaining 11/41 (27%) ASDs without GI symptoms that were characterized by HMASS for 8/11 (72%) and 7/11 (63%) were picky eaters. GM ecology was investigated for the overall ASD cohort versus CTRLs; ASDs with GI and without GI, respectively, versus CTRLs; ASD with GI versus ASD without GI; ASDs with HMASS versus low ASSs; PEs versus no-PEs; and FS versus absence of FS. In particular, the GM of ASDs, compared to CTRLs, was characterized by the increase of Proteobacteria, Bacteroidetes, Rikenellaceae, Pasteurellaceae, Klebsiella, Bacteroides, Roseburia, Lactobacillus, Prevotella, Sutterella, Staphylococcus, and Haemophilus. Moreover, Sutterella, Roseburia and Fusobacterium were associated to ASD with GI symptoms compared to CTRLs. Interestingly, ASD with GI symptoms showed higher value of zonulin and lower levels of lysozyme, which were also characterized by differentially expressed predicted functional pathways. Multiple machine learning models classified correctly 80% overall ASDs, compared with CTRLs, based on Bacteroides, Lactobacillus, Prevotella, Staphylococcus, Sutterella, and Haemophilus features. In conclusion, in our patient cohort, regardless of the evaluation of many factors potentially modulating the GM profile, the major phenotypic determinant affecting the GM was represented by GI hallmarks and patients’ age.

Background: During pregnancy, the balance between pro-inflammatory and anti-inflammatory responses is essential for ensuring healthy outcomes. Dietary Fatty acids may modulate inflammation. Methods: We investigated the association between dietary fatty acids as profiled on red blood cells membranes and a few pro- and anti-inflammatory cytokines, including the adipokines leptin and adiponectin at ~38 weeks in 250 healthy women. Results: We found a number of associations, including, but not limited to those of adiponectin with C22:3/C22:4 (coeff −1.44; p = 0.008), C18:1 c13/c14 (coeff 1.4; p = 0.02); endotoxin with C20:1 (coeff −0.9; p = 0.03), C22:0 (coeff −0.4; p = 0.05); MCP-1 with C16:0 (coeff 0.8; p = 0.04); and ICAM-1 with C14:0 (coeff −86.8; p = 0.045). Several cytokines including leptin were associated with maternal body weight (coeff 0.9; p = 2.31 × 10−5), smoking habits (i.e., ICAM-1 coeff 133.3; p = 0.09), or gestational diabetes (i.e., ICAM-1 coeff 688; p = 0.06). Conclusions: In a general cohort of pregnant women, the intake of fatty acids influenced the balance between pro- and anti-inflammatory molecules together with weight gain, smoking habits, and gestational diabetes.

Abstract Background Despite the efficacy of immune checkpoint inhibitors (ICIs) only the 20–30% of treated patients present long term benefits. The metabolic changes occurring in the gut microbiota metabolome are herein proposed as a factor potentially influencing the response to immunotherapy. Methods The metabolomic profiling of gut microbiota was characterized in 11 patients affected by non-small cell lung cancer (NSCLC) treated with nivolumab in second-line treatment with anti-PD-1 nivolumab. The metabolomics analyses were performed by GC–MS/SPME and 1H-NMR in order to detect volatile and non-volatile metabolites. Metabolomic data were processed by statistical profiling and chemometric analyses. Results Four out of 11 patients (36%) presented early progression, while the remaining 7 out of 11 (64%) presented disease progression after 12 months. 2-Pentanone (ketone) and tridecane (alkane) were significantly associated with early progression, and on the contrary short chain fatty acids (SCFAs) (i.e., propionate, butyrate), lysine and nicotinic acid were significantly associated with long-term beneficial effects. Conclusions Our preliminary data suggest a significant role of gut microbiota metabolic pathways in affecting response to immunotherapy. The metabolic approach could be a promising strategy to contribute to the personalized management of cancer patients by the identification of microbiota-linked “indicators” of early progressor and long responder patients.

Type 1 diabetes (T1D) is a chronic autoimmune metabolic disorder with onset in pediatric/adolescent age, characterized by insufficient insulin production, due to a progressive destruction of pancreatic β-cells. Evidence on the correlation between the human gut microbiota (GM) composition and T1D insurgence has been recently reported. In particular, 16S rRNA-based metagenomics has been intensively employed in the last decade in a number of investigations focused on GM representation in relation to a pre-disease state or to a response to clinical treatments. On the other hand, few works have been published using alternative functional omics, which is more suitable to provide a different interpretation of such a relationship. In this work, we pursued a comprehensive metaproteomic investigation on T1D children compared with a group of siblings (SIBL) and a reference control group (CTRL) composed of aged matched healthy subjects, with the aim of finding features in the T1D patients’ GM to be related with the onset of the disease. Modulated metaproteins were found either by comparing T1D with CTRL and SIBL or by stratifying T1D by insulin need (IN), as a proxy of β-cells damage, showing some functional and taxonomic traits of the GM, possibly related to the disease onset at different stages of severity.

Alterations of gut microbiota have been identified before clinical manifestation of type 1 diabetes (T1D). To identify the associations amongst gut microbiome profile, metabolism and disease markers, the 16S rRNA-based microbiota profiling and 1H-NMR metabolomic analysis were performed on stool samples of 52 T1D patients at onset, 17 T1D siblings and 57 healthy subjects (CTRL). Univariate, multivariate analyses and classification models were applied to clinical and -omic integrated datasets. In T1D patients and their siblings, Clostridiales and Dorea were increased and Dialister and Akkermansia were decreased compared to CTRL, while in T1D, Lachnospiraceae were higher and Collinsella was lower, compared to siblings and CTRL. Higher levels of isobutyrate, malonate, Clostridium, Enterobacteriaceae, Clostridiales, Bacteroidales, were associated to T1D compared to CTRL. Patients with higher anti-GAD levels showed low abundances of Roseburia, Faecalibacterium and Alistipes and those with normal blood pH and low serum HbA1c levels showed high levels of purine and pyrimidine intermediates. We detected specific gut microbiota profiles linked to both T1D at the onset and to diabetes familiarity. The presence of specific microbial and metabolic profiles in gut linked to anti-GAD levels and to blood acidosis can be considered as predictive biomarker associated progression and severity of T1D.

Thermal–optical analysis is widely adopted for the quantitative determination of total (TC), organic (OC), and elemental (EC) carbon in atmospheric aerosol sampled by suitable filters. Nevertheless, the methodology suffers from several uncertainties and artifacts such as the well-known issue of charring affecting the OC–EC separation. In the standard approach, the effect of the possible presence of brown carbon, BrC, in the sample is neglected. BrC is a fraction of OC, usually produced by biomass burning with a thermic behavior intermediate between OC and EC. BrC is optically active: it shows an increasing absorbance when the wavelength moves to the blue–UV region of the electromagnetic spectrum. Definitively, the thermal–optical characterization of carbonaceous aerosol should be reconsidered to address the possible BrC content in the sample under analysis. We introduce here a modified Sunset Lab Inc. EC–OC analyzer. Starting from a standard commercial instrument, the unit has been modified at the physics department of the University of Genoa (Italy), making possible the alternative use of the standard laser diode at λ=635 nm and of a new laser diode at λ=405 nm. In this way, the optical transmittance through the sample can be monitored at both wavelengths. Since at shorter wavelengths the BrC absorbance is higher, a better sensitivity to this species is gained. The modified instrument also gives the possibility to quantify the BrC concentration in the sample at both wavelengths. The new unit has been thoroughly tested, with both artificial and real-world aerosol samples: the first experiment, in conjunction with the multi-wavelength absorbance analyzer (MWAA; Massabò et al., 2013, 2015), resulted in the first direct determination of the BrC mass absorption coefficient (MAC) at λ=405 nm: MAC =23±1 m2 g−1.

The RHAPS (Redox-Activity And Health-Effects Of Atmospheric Primary And Secondary Aerosol) project was launched in 2019 with the major objective of identifying specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g., number size distributions, refractory chemical components, elemental composition) and low-time resolution analyses (e.g., oxidative potential, toxicological assays, chemical composition). Preliminary results indicate that, at the real atmospheric conditions observed (i.e., daily PM1 from less than 4 to more than 50 μg m−3), high/low mass concentrations of PM1, as well as black carbon (BC) and water soluble Oxidative Potential (WSOP,) do not necessarily translate into high/low toxicity. Notably, these findings were observed during a variety of atmospheric conditions and aerosol properties and with different toxicological assessments. Findings suggest a higher complexity in the relations observed between atmospheric aerosol and toxicological endpoints that go beyond the currently used PM1 metrics. Finally, we provide an outlook to companion papers where data will be analyzed in more detail, with the focus on source apportionment of PM1 and the role of source emissions on aerosol toxicity, the OP as a predictive variable for PM1 toxicity, and the related role of SOA possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity.

In this study, the onset and shaping of the salivary and gut microbiota in healthy newborns during the first period of life has been followed, evaluating the impact of salivary microbiota on the development of early fecal microbial communities. The microbiota of 80 salivary and 82 fecal samples that were collected from healthy newborns in the first six months of life, was investigated by 16S rRNA amplicon profiling. The microbial relationship within and between the saliva and gut ecosystems was determined by correlation heatmaps and co-occurrence networks. Streptococcus and Staphylococcus appeared as early commensals in the salivary microbiota, dominating this ecosystem through the time, while Fusobacterium, Prevotella, Porphyromonas, Granulicatella, and Veillonella were late colonizers. Enterobacteriaceae, Staphylococcus and Streptococcus were gut pioneers, followed by the anaerobic Bifidobacterium, Veillonella, Eggerthella, and Bacteroides. Streptococcus, Staphylococcus, and Veillonella were shared by the gut and saliva ecosystems. The saliva and gut microbiota seem to evolve independently, driven by local adaptation strategies, except for the oral Streptococcus and Veillonella that are involved in gut microbiota development as seeding species. This study offers a piece of knowledge on how the oral microbiota may affect the gut microbiota in healthy newborns, shedding light onto new microbial targets for the development of therapies for early life intestinal dysbiosis.

Extremely sensitive food-allergic patients may react to very small amounts of allergenic foods. Precautionary allergen labelling (PAL) warns from possible allergenic contaminations. We evaluated by oral food challenge the reactivity to a brand of PAL-labelled milk- and egg-free biscuits of children with severe milk and egg allergy. We explored the ability of proteomic methods to identify minute amounts of milk/egg allergens in such biscuits. Traces of milk and/or egg allergens in biscuits were measured by two different liquid-chromatography-mass spectrometry methods. The binding of patient’s serum with egg/milk proteins was assessed using immunoblotting. None of the patients reacted to biscuits. Egg and milk proteins were undetectable with a limit of detection of 0.6 µg/g for milk and egg (method A), and of 0.1 and 0.3 µg /g for milk and egg, respectively (method B). The immunoblots did not show milk/egg proteins in the studied biscuits. Milk/egg content of the biscuits is far lower than 4 µg of milk or egg protein per gram of product, the minimal doses considered theoretically capable of causing reactions. With high sensitivity, proteomic assessments predict the harmlessness of very small amount of allergens in foods, and can be used to help avoiding unnecessary PAL.

A healthy diet during pregnancy is pivotal for the offspring health at birth and later in life. N-3 polyunsaturated fatty acids (n-3 PUFAs) are not endogenously produced in humans and are exclusively derived from the diet. They are pivotal for the fetus growth and neuronal development and seem beneficial in reducing the risk of cardiometabolic diseases and preventing later allergic disorders in the offspring by modulating the inflammatory immune response. In the present study, we investigated the association between maternal intakes of n-3PUFAs, profiled on maternal erythrocyte membranes at pregnancy term, and offspring DNA methylation on cord blood mononuclear cells in a sample of 118 mother–newborn pairs randomly drawn from the “Feeding fetus’ low-grade inflammation and insulin-resistance” study cohort. N-3 PUFA content on erythrocyte membranes is a validated biomarker to measure objectively medium term intake of n-3 PUFAs. Based on distribution of n-3 PUFA in the whole cohort of mothers, we identified mothers with low (n-3 PUFA concentration 75th percentile). The HumanMethylation450 BeadChip (Illumina) was used for the epigenome-wide association study using the Infinium Methylation Assay. The overall DNA methylation level was not different between the three groups while there was significant difference in methylation levels at certain sites. Indeed, 8,503 sites had significantly different methylations between low and high n-3 PUFA groups, 12,716 between low and medium n-3 PUFA groups, and 18,148 between high and medium n-3 PUFA groups. We found differentially methylated genes that belong prevalently to pathways of signal transduction, metabolism, downstream signaling of G protein-coupled receptors, and gene expression. Within these pathways, we identified four differentially methylated genes, namely, MSTN, IFNA13, ATP8B3, and GABBR2, that are involved in the onset of insulin resistance and adiposity, innate immune response, phospholipid translocation across cell membranes, and mechanisms of addiction to high fat diet, alcohol, and sweet taste. In conclusion, findings of this preliminary investigation suggest that maternal intake of n-3 PUFAs during pregnancy has potential to influence the offspring DNA methylation. Validation of results in a larger cohort and investigation of biological significance and impact on the phenotype are warranted.

Food allergy (FA) and, in particular, IgE-mediated cow’s milk allergy is associated with compositional and functional changes of gut microbiota. In this study, we compared the gut microbiota of cow’s milk allergic (CMA) infants with that of cow’s milk sensitized (CMS) infants and Healthy controls. The effect of the intake of a mixture of Bifidobacterium longum subsp. longum BB536, Bifidobacterium breve M-16V and Bifidobacterium longum subsp. infantis M-63 on gut microbiota modulation of CMA infants and probiotic persistence was also investigated. Gut microbiota of CMA infants resulted to be characterized by a dysbiotic status with a prevalence of some bacteria as Haemophilus, Klebsiella, Prevotella, Actinobacillus and Streptococcus. Among the three strains administered, B.longum subsp. infantis colonized the gastrointestinal tract and persisted in the gut microbiota of infants with CMA for 60 days. This colonization was associated with perturbations of the gut microbiota, specifically with the increase of Akkermansia and Ruminococcus. Multi-strain probiotic formulations can be studied for their persistence in the intestine by monitoring specific bacterial probes persistence and exploiting microbiota profiling modulation before the evaluation of their therapeutic effects.

Long-term enteral nutrition (LTEN) can induce gut microbiota (GM) dysbiosis and gastrointestinal related symptoms, such as constipation or diarrhoea. To date, the treatment of constipation is based on the use of laxatives and prebiotics. Only recently have probiotics and synbiotics been considered, the latter modulating the GM and regulating intestinal functions. This randomized open-label intervention study evaluated the effects of synbiotic treatment on the GM profile, its functional activity and on intestinal functions in long-term home EN (LTHEN) patients. Twenty LTHEN patients were recruited to take enteral formula plus one sachet/day of synbiotic (intervention group, IG) or enteral formula (control group, CG) for four months and evaluated for constipation, stool consistency, and GM and metabolite profiles. In IG patients, statistically significant reduction of constipation and increase of stool consistency were observed after four months (T1), compared to CG subjects. GM ecology analyses revealed a decrease in the microbial diversity of both IC and CG groups. Biodiversity increased at T1 for 5/11 IG patients and Methanobrevibacter was identified as the biomarker correlated to the richness increase. Moreover, the increase of short chain fatty acids and the reduction of harmful molecules have been correlated to synbiotic administration. Synbiotics improve constipation symptoms and influences Methanobrevibacter growth in LTHEN patients.

Background: Identification, quantification and typing of MProteins (MP) play an important role in the diagnosis, classification and monitoring of monoclonal gammopathies both of malignant origin (eg. Multiple Myeloma) and of unknown origin. Previous evidence attests that MGUS (Monoclonal Gammopathy of Undetermined Significance) detected by agarose gel electrophoresis has a prevalence of 3.2% in the general population. Therefore, our study aimed to verify this data by means of capillary zone electrophoresis (CZE). Methods: CZE was performed to evaluate the prevalence of M-Protein (MP) in 44.474 consecutive outpatients of all ages with a prescription for serum protein electrophoresis over a 2-year period (2008 and 2009). All MPs that were identified were then typed by immunofixation electrophoresis on agarose gel (IFE). Results: In subjects aged over 50 (23.408, i.e., 52.6% of the whole cohort) MP 90 (2%) and

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children. Herein, we evaluated the relationship between the gut microbiome (GM) and disease phenotype by an integrated omics fused approach. In a multicenter, observational cohort study, stools from Italian JIA patients were collected at baseline, active, and inactive disease stages, and their GM compared to healthy controls (CTRLs). The microbiota metabolome was analyzed to detect volatile- and non-volatile organic compounds (VOCs); the data were fused with operational taxonomic units (OTUs) from 16S RNA targeted-metagenomics and classified by chemometric models. Non-VOCs did not characterize JIA patients nor JIA activity stages compared to CTRLs. The core of VOCs, (Ethanol, Methyl-isobutyl-ketone, 2,6-Dimethyl-4-heptanone and Phenol) characterized patients at baseline and inactive disease stages, while the OTUs represented by Ruminococcaceae, Lachnospiraceae and Clostridiacea discriminated between JIA inactive stage and CTRLs. No differences were highlighted amongst JIA activity stages. Finally, the fused data discriminated inactive and baseline stages versus CTRLs, based on the contribution of the invariant core of VOCs while Ruminococcaceae concurred for the inactive stage versus CTRLs comparison. In conclusion, the GM signatures enabled to distinguish the inactive disease stage from CTRLs.

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

The human gut contains trillions of microbes that play a central role in host biology, including the provision of key nutrients from the diet. Food is a major source of precursors for metabolite production; in fact, diet modulates the gut microbiota (GM) as the nutrients, derived from dietary intake, reach the GM, affecting both the ecosystem and microbial metabolic profile. GM metabolic ability has an impact on human nutritional status from childhood. However, there is a wide variability of dietary patterns that exist among individuals. The study of interactions with the host via GM metabolic pathways is an interesting field of research in medicine, as microbiota members produce myriads of molecules with many bioactive properties. Indeed, much evidence has demonstrated the importance of metabolites produced by the bacterial metabolism from foods at the gut level that dynamically participate in various biochemical mechanisms of a cell as a reaction to environmental stimuli. Hence, the GM modulate homeostasis at the gut level, and the alteration in their composition can concur in disease onset or progression, including immunological, inflammatory, and metabolic disorders, as well as cancer. Understanding the gut microbe–nutrient interactions will increase our knowledge of how diet affects host health and disease, thus enabling personalized therapeutics and nutrition.

BackgroundCystic fibrosis (CF) is a disorder affecting the respiratory, digestive, reproductive systems and sweat glands. This lethal hereditary disease has known or suspected links to the dysbiosis gut microbiota. High-throughput meta-omics-based approaches may assist in unveiling this complex network of symbiosis modifications.ObjectivesThe aim of this study was to provide a predictive and functional model of the gut microbiota enterophenotype of pediatric patients affected by CF under clinical stability.MethodsThirty-one fecal samples were collected from CF patients and healthy children (HC) (age range, 1-6 years) and analysed using targeted-metagenomics and metabolomics to characterize the ecology and metabolism of CF-linked gut microbiota. The multidimensional data were low fused and processed by chemometric classification analysis.ResultsThe fused metagenomics and metabolomics based gut microbiota profile was characterized by a high abundance of Propionibacterium, Staphylococcus and Clostridiaceae, including Clostridium difficile, and a low abundance of Eggerthella, Eubacterium, Ruminococcus, Dorea, Faecalibacterium prausnitzii, and Lachnospiraceae, associated with overexpression of 4-aminobutyrate (GABA), choline, ethanol, propylbutyrate, and pyridine and low levels of sarcosine, 4-methylphenol, uracil, glucose, acetate, phenol, benzaldehyde, and methylacetate. The CF gut microbiota pattern revealed an enterophenotype intrinsically linked to disease, regardless of age, and with dysbiosis uninduced by reduced pancreatic function and only partially related to oral antibiotic administration or lung colonization/infection.ConclusionsAll together, the results obtained suggest that the gut microbiota enterophenotypes of CF, together with endogenous and bacterial CF biomarkers, are direct expression of functional alterations at the intestinal level. Hence, it's possible to infer that CFTR impairment causes the gut ecosystem imbalance.This new understanding of CF host-gut microbiota interactions may be helpful to rationalize novel clinical interventions to improve the affected children's nutritional status and intestinal function.

The human gut has been continuously exposed to a broad spectrum of intestinal organisms, including viruses, bacteria, fungi, and parasites (protozoa and worms), over millions of years of coevolution, and plays a central role in human health. The modern lifestyles of Western countries, such as the adoption of highly hygienic habits, the extensive use of antimicrobial drugs, and increasing globalisation, have dramatically altered the composition of the gut milieu, especially in terms of its eukaryotic "citizens." In the past few decades, numerous studies have highlighted the composition and role of human intestinal bacteria in physiological and pathological conditions, while few investigations exist on gut parasites and particularly on their coexistence and interaction with the intestinal microbiota. Studies of the gut "parasitome" through "omic" technologies, such as (meta)genomics, transcriptomics, proteomics, and metabolomics, are herein reviewed to better understand their role in the relationships between intestinal parasites, host, and resident prokaryotes, whether pathogens or commensals. Systems biology-based profiles of the gut "parasitome" under physiological and severe disease conditions can indeed contribute to the control of infectious diseases and offer a new perspective of omics-assisted tropical medicine.

The Mediterranean diet (MD) is considered one of the healthiest dietary models. Many of the characteristic components of the MD have functional features with positive effects on health and wellness. The MD adherence, calculated through various computational scores, can lead to a reduction of the incidence of major diseases (e.g., cancers, metabolic and cardiovascular syndromes, neurodegenerative diseases, type 2 diabetes and allergy). Furthermore, eating habits are the main significant determinants of the microbial multiplicity of the gut, and dietary components influence both microbial populations and their metabolic activities from the early stages of life. For this purpose, we present a study proposal relying on the generation of individual gut microbiota maps from MD-aware children/adolescents. The maps, based on meta-omics approaches, may be considered as new tools, acting as a systems biology-based proof of evidence to evaluate MD effects on gut microbiota homeostasis. Data integration of food metabotypes and gut microbiota “enterotypes” may allow one to interpret MD adherence and its effects on health in a new way, employable for the design of targeted diets and nutraceutical interventions in childcare and clinical management of food-related diseases, whose onset has been significantly shifted early in life.

Polyunsaturated fatty acids (PUFAs) are required to maintain the fluidity, permeability and integrity of cell membranes. Maternal dietary supplementation with ω-3 PUFAs during pregnancy has beneficial effects, including increased gestational length and reduced risk of pregnancy complications. Significant amounts of ω-3 docosahexaenoic acid (DHA) are transferred from maternal to fetal blood, hence ensuring high levels of DHA in the placenta and fetal bloodstream and tissues. Fetal DHA demand increases exponentially with gestational age, especially in the third trimester, due to fetal development. According to the World Health Organization (WHO) and the Food and Agriculture Organization of the United Nations (FAO), a daily intake of DHA is recommended during pregnancy. Omega-3 PUFAs are involved in several anti-inflammatory, pro-resolving and anti-oxidative pathways. Several placental disorders, such as intrauterine growth restriction, premature rupture of membranes (PROM) and preterm-PROM (pPROM), are associated with placental inflammation and oxidative stress. This pilot study reports on a preliminary evaluation of the significance of the daily DHA administration on PROM and pPROM events in healthy pregnant women. Further extensive clinical trials will be necessary to fully elucidate the correlation between DHA administration during pregnancy and PROM/pPROM occurrence, which is related in turn to gestational duration and overall fetal health.