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Chronic obstructive pulmonary disease (COPD) caused by cigarette smoke (CS) is featured by oxidative stress and chronic inflammation. Due to the poor efficacy of standard glucocorticoid therapy, new treatments are required. Here, we investigated whether the novel compound SUL-151 with mitoprotective properties can be used as a prophylactic and therapeutic treatment in a murine CS-induced inflammation model. SUL-151 (4 mg/kg), budesonide (500 μg/kg), or vehicle were administered via oropharyngeal instillation in this prophylactic and therapeutic treatment setting. The number of immune cells was determined in the bronchoalveolar lavage fluid (BALF). Oxidative stress response, mitochondrial adenosine triphosphate (ATP) production, and mitophagy-related proteins were measured in lung homogenates. SUL-151 significantly decreased more than 70% and 50% of CS-induced neutrophils in BALF after prophylactic and therapeutic administration, while budesonide showed no significant reduction in neutrophils. Moreover, SUL-151 prevented the CS-induced decrease in ATP and mitochondrial mtDNA and an increase in putative protein kinase 1 expression in the lung homogenates. The concentration of SUL-151 was significantly correlated with malondialdehyde level and radical scavenging activity in the lungs. SUL-151 inhibited the increased pulmonary inflammation and mitochondrial dysfunction in this CS-induced inflammation model, which implied that SUL-151 might be a promising candidate for COPD treatment.

Supplemental material, sj-pdf-6-tar-10.1177_1753466620961696 for Higher prescription of antidepressants and/or anxiolytics among chronic obstructive pulmonary disease patients by Charlotte E. Pelgrim, Jan Maurik van den Heuvel, Gert Folkerts, Johan Garssen, Anke H. Maitland-van der Zee and Aletta D. Kraneveld in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-4-tar-10.1177_1753466620961696 for Higher prescription of antidepressants and/or anxiolytics among chronic obstructive pulmonary disease patients by Charlotte E. Pelgrim, Jan Maurik van den Heuvel, Gert Folkerts, Johan Garssen, Anke H. Maitland-van der Zee and Aletta D. Kraneveld in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-3-tar-10.1177_1753466620961696 for Higher prescription of antidepressants and/or anxiolytics among chronic obstructive pulmonary disease patients by Charlotte E. Pelgrim, Jan Maurik van den Heuvel, Gert Folkerts, Johan Garssen, Anke H. Maitland-van der Zee and Aletta D. Kraneveld in Therapeutic Advances in Respiratory Disease

Autism Spectrum Disorder (ASD) is a spectrum of disorders that are characterized by problems in social interaction and repetitive behavior. The disease is thought to develop from changes in brain development at an early age, although the exact mechanisms are not known yet. In addition, a significant number of people with ASD develop problems in the intestinal tract. A Disintegrin And Metalloproteases (ADAMs) include a group of enzymes that are able to cleave membrane-bound proteins. ADAM10 and ADAM17 are two members of this family that are able to cleave protein substrates involved in ASD pathogenesis, such as specific proteins important for synapse formation, axon signaling and neuroinflammation. All these pathological mechanisms are involved in ASD. Besides the brain, ADAM10 and ADAM17 are also highly expressed in the intestines. ADAM10 and ADAM17 have implications in pathways that regulate gut permeability, homeostasis and inflammation. These metalloproteases might be involved in microbiota-gut–brain axis interactions in ASD through the regulation of immune and inflammatory responses in the intestinal tract. In this review, the potential roles of ADAM10 and ADAM17 in the pathology of ASD and as targets for new therapies will be discussed, with a focus on the gut–brain axis.

International audience; Modern genomic sequencing machines can measure thousands of probes from different specimens. Nevertheless, theoretically comparable datasets can show considerably distinguishable properties, depending on both platform and specimen, a phenomenon known as batch effect. Batch correction is the technique aiming at removing this effect from the data. A possible approach to batch correction is to find a transformation function between different datasets, but optimizing the weights of such a function is not trivial: As there is no explicit gradient to follow, traditional optimization techniques would fail. In this work, we propose to use a state-of-the-art evolutionary algorithm, Covariance Matrix Adaptation Evolution Strategy, to optimize the weights of a transformation function for batch correction. The fitness function is driven by the classification accuracy of an ensemble of algorithms on the transformed data. The case study selected to test the proposed approach is mRNA gene expression data of Chronic Fatigue Syndrome, a disease for which there is currently no established diagnostic test. The transformation function obtained from three datasets, produced from different specimens, remarkably improves the performance of classifiers on the task of diagnosing Chronic Fatigue. The presented results are an important steppingstone towards a reliable diagnostic test for this syndrome.

An increasing number of studies are focusing on the inflammatory response to alcohol as a potentially important determinant of hangover severity. In this article, data from two studies were re-evaluated to investigate the relationship between hangover severity and relevant biomarkers of alcohol metabolism, oxidative stress and the inflammatory response to alcohol. Hangover severity was significantly and positively correlated with blood concentrations of biomarkers of the inflammatory response to alcohol, in particular, Interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-&alpha, ) and C-reactive protein (CRP). At 4 h after alcohol consumption, blood ethanol concentration (but not acetaldehyde) was significantly and positively associated with elevated levels of IL-6, suggesting a direct inflammatory effect of ethanol. In addition, biomarkers of oxidative stress, i.e., malondialdehyde and 8-isoprostrane, were significantly correlated with hangover severity, suggesting that oxidative stress also contributes to the inflammatory response. The timing of the assessments suggests initial slow elimination of ethanol in the first hours after alcohol consumption. As a consequence, more ethanol is present in the second half of the night and the next morning, which will elicit more oxidative stress and a more profound inflammatory response. Together, these processes result in more severe hangovers.

One of the reasons for the fast spread of SARS-CoV-2 is the lack of accuracy in detection tools in the clinical field. Molecular techniques, such as quantitative real-time RT-PCR and nucleic acid sequencing methods, are widely used to identify pathogens. For this particular virus, however, they have an overall unsatisfying detection rate, due to its relatively recent emergence and still not completely understood features. In addition, SARS-CoV-2 is remarkably similar to other Coronaviruses, and it can present with other respiratory infections, making identification even harder. To tackle this issue, we propose an assisted detection test, combining molecular testing with deep learning. The proposed approach employs a state-of-the-art deep convolutional neural network, able to automatically create features starting from the genome sequence of the virus. Experiments on data from the Novel Coronavirus Resource (2019nCoVR) show that the proposed approach is able to correctly classify SARS-CoV-2, distinguishing it from other coronavirus strains, such as MERS-CoV, HCoV-NL63, HCoV-OC43, HCoV-229E, HCoV-HKU1, and SARS-CoV regardless of missing information and errors in sequencing (noise). From a dataset of 553 complete genome non-repeated sequences that vary from 1,260 to 31,029 bps in length, the proposed approach classifies the different coronaviruses with an average accuracy of 98.75% in a 10-fold cross-validation, identifying SARS-CoV-2 with an AUC of 98%, specificity of 0.9939 and sensitivity of 1.00 in a binary classification. Then, using the same basis, we classify SARS-CoV-2 from 384 complete viral genome sequences with human host, that contain the gene ORF1ab from the NCBI with a 10-fold accuracy of 98.17% , a specificity of 0.9797 and sensitivity of 1.00. These preliminary results seem encouraging enough to identify deep learning as a promising research venue to develop assisted detection tests for SARS-CoV-2. At this end the interaction between viromics and deep learning , will hopefully help to solve global infection problems. In addition, we offer our code and processed data to be used for diagnostic purposes by medical doctors, virologists and scientists involved in solving the SARS-CoV-2 pandemic. As more data become available we will update our system.

International audience; Circulating microRNAs (miRNA) are small noncoding RNA molecules that can be detected in bodily fluids without the need for major invasive procedures on patients. miRNAs have shown great promise as biomarkers for tumors to both assess their presence and to predict their type and subtype. Recently, thanks to the availability of miRNAs datasets, machine learning techniques have been successfully applied to tumor classification. The results, however, are difficult to assess and interpret by medical experts because the algorithms exploit information from thousands of miRNAs. In this work, we propose a novel technique that aims at reducing the necessary information to the smallest possible set of circulating miRNAs. The dimensionality reduction achieved reflects a very important first step in a potential, clinically actionable, circulating miRNA-based precision medicine pipeline. While it is currently under discussion whether this first step can be taken, we demonstrate here that it is possible to perform classification tasks by exploiting a recursive feature elimination procedure that integrates a heterogeneous ensemble of high-quality, state-of-the-art classifiers on circulating miRNAs. Heterogeneous ensembles can compensate inherent biases of classifiers by using different classification algorithms. Selecting features then further eliminates biases emerging from using data from different studies or batches, yielding more robust and reliable outcomes. The proposed approach is first tested on a tumor classification problem in order to separate 10 different types of cancer, with samples collected over 10 different clinical trials, and later is assessed on a cancer subtype classification task, with the aim to distinguish triple negative breast cancer from other subtypes of breast cancer. Overall, the presented methodology proves to be effective and compares favorably to other state-of-the-art feature selection methods.

International audience; Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting 1 in 160 people in the world. Although there is a strong genetic heritability to ASD, it is now accepted that environmental factors can play a role in its onset. As the prevalence of gastrointestinal (GI) symptoms is four-times higher in ASD patients, the potential implication of the gut microbiota in this disorder is being increasingly studied. A disturbed microbiota composition has been demonstrated in ASD patients, accompanied by altered production of bacterial metabolites. Clinical studies as well as preclinical studies conducted in rodents have started to investigate the physiological functions that gut microbiota might disturb and thus underlie the pathophysiology of ASD. The first data support an involvement of the immune system and tryptophan metabolism, both in the gut and central nervous system. In addition, a few clinical studies and a larger number of preclinical studies found that modulation of the microbiota through antibiotic and probiotic treatments, or fecal microbiota transplantation, could improve behavior. Although the understanding of the role of the gut microbiota in the physiopathology of ASD is only in its early stages, the data gathered in this review highlight that this role should be taken in consideration.

The future of food is one of the major world-wide challenges. In this perspective paper, we set-up a framework for a multi-disciplinary future food systems approach, building on the UN Sustainable Development Goals. We hereby combine a truly sustainable approach including social science aspects combined with the One Health approach. Scientists from a large number of backgrounds have addressed four key areas that are discussed in more detail in this paper: (i) nature inspired food production, (ii) sustainable immune resilience, (iii) social and cultural change of food behavior, and (iv) food fairness. We believe that transformations to integrated future food system approaches should move beyond single solutions and can only be solved by working in transdisciplinary settings of science, society, and industry.

OBJECTIVE: The intestinal microbiota is acknowledged to be essential in brain development and behaviour. Their composition can be modulated by prebiotics such as short-chain galacto-oligosaccharides (scGOS) and long-chain fructo-oligosaccharide (lcFOS). Several studies reported potential health benefit of prebiotics on behaviour. As the prebiotic mixture of scGOS and lcFOS is included in infant formula, we investigated the effects of dietary supplementation with this specific mixture from the day of birth onwards on behaviour and intestinal microbiota development in mice. METHOD: Healthy male BALB/cByJ mice received, from day of birth, a dietary supplement with or without 3% scGOS:lcFOS (9:1). Behavioural tests were performed pre-weaning, in adolescence, early adulthood and adulthood. We assessed faecal microbiota compositions over time, caecal short-chain fatty acids as well as brain mRNA expression of Htr1a, Htr1b and Tph2 and monoamine levels. RESULTS: Compared to control fed mice, scGOS:lcFOS fed mice showed reduced anxiety-like and repetitive behaviour over time and improved social behaviour in adulthood. The serotonergic system in the prefrontal cortex (PFC) and somatosensory cortex (SSC) was affected by the scGOS:lcFOS. In the PFC, mRNA expression of brain-derived neurotrophic factor (Bdnf) was enhanced in scGOS:lcFOS fed mice. Although the bacterial diversity of the intestinal microbiota was unaffected by the scGOS:lcFOS diet, microbiota composition differed between the scGOS:lcFOS and the control fed mice over time. Moreover, an increased saccharolytic and decreased proteolytic fermentation activity were observed in caecum content. DISCUSSION: Supplementing the diet with scGOS:lcFOS from the day of birth is associated with reduced anxiety-like and improved social behaviour during the developmental period and later in life, and modulates the composition and activity of the intestinal microbiota in healthy male BALB/c mice. These data provide further evidence of the potential impact of scGOS:lcFOS on behaviour at several developmental stages throughout life and strengthen the insights in the interplay between the developing intestine and brain.

The self-assessment of perceived immune status is important, as this subjective observation leads individuals to decide whether or not to seek medical help or adapt their lifestyle. In addition, it can be used in clinical settings and research. The aim of this series of studies was to develop and validate a short questionnaire to assess perceived immune functioning. Five surveys were conducted among Dutch and International young healthy adults (18&ndash, 30 years old), and two others among older age groups with various health complaints. For the first study, an existing immune functioning scale was modified and elaborated resulting in 23 immune-health-related items, of which the occurrence was rated on a 5-point Likert scale. A student sample was surveyed, and the results were used to shorten the 23-item listing into a 7-item scale with a predictive validity of 85%. Items include &ldquo, sudden high fever&rdquo, &ldquo, diarrhea&rdquo, headache&rdquo, skin problems (e.g., acne and eczema)&rdquo, muscle and joint pain&rdquo, common cold&rdquo, and &ldquo, coughing&rdquo, The scale is named Immune Status Questionnaire (ISQ), and it aims to assess perceived immune status over the preceding year. The second study revealed that the ISQ score correlated significantly with a 1-item perceived immune functioning (r = 0.383, p &lt, 0.0001). In the third study, the final Likert scale descriptors were determined (&ldquo, never&rdquo, sometimes&rdquo, regularly&rdquo, often&rdquo, (almost) always)&rdquo, The fourth study showed that the test&ndash, retest reliability of the ISQ is acceptable (r = 0.80). The fifth study demonstrated the association of ISQ scores with various neuropsychological and health correlates in an international sample, including perceived health and immune fitness, as well as levels of stress, fatigue, depression and anxiety. Study 6 demonstrated significant associations between ISQ scores and experiencing irritable bowel syndrome (IBS) symptoms in a sample of insomnia patients. Study 7 compared the effect of a dietary intervention in participants reporting &ldquo, poor health&rdquo, versus &ldquo, normal health&rdquo, It is shown that ISQ scores can differentiate between those with poor and normal health, and that an effective intervention is associated with a significant improvement in ISQ scores. Data from Study 7 were further used to determine an ISQ cut-off value for reduced immune functioning, and a direct comparison with 1-item perceived immune functioning scores enabled constructing the final scoring format of the ISQ. In conclusion, the ISQ has appropriate face, content, and construct validity and is a reliable, stable and valid method to assess the past 12 month&rsquo, s perceived immune status.

Deoxynivalenol, T-2 toxin, and zearalenone, major Fusarium mycotoxins, contaminate human food on a global level. Exposure to these mycotoxins during pregnancy can lead to abnormalities in neonatal development. Therefore, the aim of this study was to investigate the effects of Fusarium mycotoxins on human placental epithelial cells. As an in vitro model of placental barrier, BeWo cells were exposed to different concentrations of deoxynivalenol, zearalenone or T-2 toxin. Cytotoxicity, effects on barrier integrity, paracellular permeability along with mRNA and protein expression and localization of junctional proteins after exposure were evaluated. Induction of proinflammatory responses was determined by measuring cytokine production. Increasing mycotoxin concentrations affect BeWo cell viability, and T-2 toxin was more toxic compared to other mycotoxins. Deoxynivalenol and T-2 toxin caused significant barrier disruption, altered protein and mRNA expression of junctional proteins, and induced irregular cellular distribution. Although the effects of zearalenone on barrier integrity were less prominent, all tested mycotoxins were able to induce inflammation as measured by IL-6 release. Overall, Fusarium mycotoxins disrupt the barrier of BeWo cells by altering the expression and structure of junctional proteins and trigger proinflammatory responses. These changes in placental barrier may disturb the maternal&ndash, fetal interaction and adversely affect fetal development.