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Contents Undernutrition before and after calving has a detrimental effect on the fertility of dairy cows. The effect of nutritional stress was previously reported to influence gene expression in key tissues for metabolic health and reproduction such as the liver and the genital tract early after calving, but not at breeding, that is, between 70 and 90 days post-partum. This study investigated the effects of pre- and post-partum mild underfeeding on global gene expression in the oviduct, endometrium and corpus luteum of eight multiparous Holstein cows during the early and middle phases of an induced cycle 80 days post-partum. Four control cows received 100% of energy and protein requirements during the dry period and after calving, while four underfed received 80% of control diet. Oestrous synchronization treatment was used to induce ovulation on D80 post-partum. Oviducts, ovaries and the anterior part of each uterine horn were recovered surgically 4, 8, 12 and 15 days after ovulation. Corpora lutea were dissected from the ovaries, and the endometrium was separated from the stroma and myometrium in each uterine horn. The oviduct segments were comprised of ampulla and isthmus. RNAs from ipsi- and contralateral samples were pooled on an equal weight basis. In each tissue, gene expression was assessed on a custom bovine 10 K array. No differentially expressed gene ( DEG) in the corpus luteum was identified between underfed and control, conversely to 293 DEGs in the oviduct vs 1 in the endometrium under a false discovery rate ( FDR) < 0.10 and 1370 DEGs vs 3, respectively, under FDR < 0.15. Additionally, we used dedicated statistics (regularized canonical correlation analysis) to correlate the post-partum patterns of six plasma metabolites and hormones related to energy metabolism measured weekly between calving and D80 with gene expression. High correlations were observed between post-partum patterns of IGF-1, insulin, β-hydroxybutyrate and the expression in the oviduct of genes related to reproductive system disease, connective tissue disorders and metabolic disease. Moreover, we found special interest in the literature to retinoic acid-related genes (e.g. FABP5/ CRABP2) that might indicate abnormalities in post-partum tissue repair mechanisms. In conclusion, this experiment highlights relationships between underfeeding and gene expression in the oviduct and endometrium after ovulation in cyclic Holstein cows. This might help to explain the effect of mild undernutrition on fertilization failure and early embryonic mortality in post-partum dairy cows. [ABSTRACT FROM AUTHOR]

Abstract The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.

Abstract A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.

Aircraft structures are commonly subjected to repeated loading cycles leading to fatigue damage. Fatigue data can be extrapolated by fatigue models which are adopted to describe the fatigue damage behaviour. Such models depend on their parameters for accurate prediction of the fatigue life. Therefore, several methods have been developed for estimating the model parameters for both linear and nonlinear systems. It is useful for a broad class of parameter identification problems when the dynamic model is not known. In this paper, the Paris law is used as fatigue-crack-length growth model on a metallic component under loading cycles. The Extended Kalman Filter (EKF) is proposed as estimation method. Simulated crack length data is used to validate the estimation method. Based on experimental data obtained from fatigue experiment, the crack length and model parameters are estimated. Accurate model parameters allow a more realistic prediction of the fatigue life, consequently, the remaining useful life (RUL) of component can be accurately computed. In this sense, maintenance performance could be improved.

Abstract Background Since 2001, the use of more and more dense maps has made researchers aware that combining linkage and linkage disequilibrium enhances the feasibility of fine-mapping genes of interest. So, various method types have been derived to include concepts of population genetics in the analyses. One major drawback of many of these methods is their computational cost, which is very significant when many markers are considered. Recent advances in technology, such as SNP genotyping, have made it possible to deal with huge amount of data. Thus the challenge that remains is to find accurate and efficient methods that are not too time consuming. The study reported here specifically focuses on the half-sib family animal design. Our objective was to determine whether modelling of linkage disequilibrium evolution improved the mapping accuracy of a quantitative trait locus of agricultural interest in these populations. We compared two methods of fine-mapping. The first one was an association analysis. In this method, we did not model linkage disequilibrium evolution. Therefore, the modelling of the evolution of linkage disequilibrium was a deterministic process; it was complete at time 0 and remained complete during the following generations. In the second method, the modelling of the evolution of population allele frequencies was derived from a Wright-Fisher model. We simulated a wide range of scenarios adapted to animal populations and compared these two methods for each scenario. Results Our results indicated that the improvement produced by probabilistic modelling of linkage disequilibrium evolution was not significant. Both methods led to similar results concerning the location accuracy of quantitative trait loci which appeared to be mainly improved by using four flanking markers instead of two. Conclusions Therefore, in animal half-sib designs, modelling linkage disequilibrium evolution using a Wright-Fisher model does not significantly improve the accuracy of the QTL location when compared to a simpler method assuming complete and constant linkage between the QTL and the marker alleles. Finally, given the high marker density available nowadays, the simpler method should be preferred as it gives accurate results in a reasonable computing time.

Resumo Contexto O edema ocupacional (EO) de membros inferiores (MMII) é um importante fator de queda na qualidade de vida, e a sua prevenção impõe a prescrição de medidas profiláticas, como o uso de meias de compressão (MCs). Objetivos Avaliar a efetividade das MCs na prevenção do EO e a sua repercussão na qualidade de vida de cabeleireiras. Métodos Este ensaio clínico realizou medidas de tornozelo e panturrilha de 38 cabeleireiras sem doença venosa no início e no final da jornada de trabalho em um momento sem e em outro usando MCs. Também responderam um questionário sobre sintomas e qualidade de vida em doença venosa. Resultados Os valores do ponto B foram de 21,1±2,2 cm no momento inicial sem meias, 22,1±2,3 cm no momento final sem meias (p = 0,0001 em relação ao inicial sem meias), e 21,2±2,1 cm no momento final com meias (p = 0,0001 em relação ao final sem meias). Não foi significante a diferença entre os valores médios do ponto B inicial sem meias e final com meias (p=0,324), ou seja, não houve formação de edema nos MMII ao final da jornada de trabalho em ortostatismo prolongado quando em uso de MCs. Pôde-se observar melhora da limitação sobre as atividades laborais (p = 0,0001), domésticas (p = 0,008) e de lazer ou sociais em pé (p = 0,0001). Conclusões As MCs são efetivas na prevenção do EO de MMII, e a atenuação de sintomas como dor e fadiga contribui diretamente para melhor qualidade de vida de cabeleireiras.

Resumo A ruptura do aneurisma de aorta abdominal é um evento com alta mortalidade, e o seu tratamento nesses casos é uma emergência médica. O tratamento endovascular desses aneurismas tem se estabelecido como uma alternativa minimamente invasiva à cirurgia aberta clássica, tornando-se a opção de primeira escolha. Contudo, 20 a 50% dos pacientes portadores de aneurisma de aorta abdominal não apresentam anatomia favorável para o tratamento endovascular devido à presença de colo curto ou pelo acometimento de ramos viscerais pelo aneurisma. Relatamos um caso de uma paciente de 70 anos submetida à correção endovascular de aneurisma roto justarrenal com implante de stents paralelos para as renais (técnica de chaminé). São apresentados dados clínicos e detalhes do procedimento. O sucesso técnico foi obtido e não houve relato de complicações pós-operatórias.

Resumo A dor pélvica crônica é uma doença debilitante, com impacto na qualidade de vida e custos para os serviços de saúde. A síndrome de quebra-nozes é uma importante causa dessa dor, e se refere a um conjunto de sinais secundários à compressão da veia renal esquerda, mais comumente entre a artéria mesentérica superior e a aorta. Seu tratamento ainda permanece controverso e varia de acordo com a gravidade clínica do paciente. Contudo, a técnica endovascular com implante de stent em veia renal tem obtido excelentes resultados. Relatamos um caso de uma paciente de 59 anos submetida a correção endovascular com stent autoexpansível de nitinol. São apresentados dados clínicos, detalhes do procedimento e resultados do acompanhamento dessa paciente. O sucesso técnico foi obtido e não houve relato de complicações pós-operatórias. Pôde-se observar alívio dos sintomas e melhora nos exames de imagem realizados no acompanhamento de curto prazo.

Wheat proteins can trigger immunogenic reactions due to their resistance to digestion and immunostimulatory epitopes. Here, we investigated the peptidomic map of partially digested bread samples and the fingerprint of epitope diversity from 16 wheat genotypes grown in two environmental conditions. Flour protein content and composition were characterized; gastric and jejunal peptides were quantified using LC-MS/MS, and genotypes were classified into high or low bread protein digestibility. Differences in flour protein content and peptide composition distinguish high from low digestibility genotypes in both growing environments. No common peptide signature was found between high- and low-digestible genotypes; however, the celiac or allergen epitopes were noted not to be higher in low-digestible genotypes. Overall, this study established a peptidomic and epitope diversity map of digested wheat bread and provided new insights and correlations between weather conditions, genotypes, digestibility and wheat sensitivities such as celiac disease and wheat allergy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 French National Institute for Agricultural Research INRAE. Published by Elsevier Ltd.. All rights reserved.)

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD., (© 2023 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)

Background: The ongoing evolution of the Next Generation Sequencing (NGS) technologies has led to the production of genomic data on a massive scale. While tools for genomic data integration and analysis are becoming increasingly available, the conceptual and analytical complexities still represent a great challenge in many biological contexts., Results: To address this issue, we describe a six-steps tutorial for the best practices in genomic data integration, consisting of (1) designing a data matrix; (2) formulating a specific biological question toward data description, selection and prediction; (3) selecting a tool adapted to the targeted questions; (4) preprocessing of the data; (5) conducting preliminary analysis, and finally (6) executing genomic data integration., Conclusion: The tutorial has been tested and demonstrated on publicly available genomic data generated from poplar (Populus L.), a woody plant model. We also developed a new graphical output for the unsupervised multi-block analysis, cimDiablo&#95;v2, available at https://forgemia.inra.fr/umr-gdec/omics-integration-on-poplar , and allowing the selection of master drivers in genomic data variation and interplay., (© 2024. The Author(s).)

Background: The rapid development of omics acquisition techniques has induced the production of a large volume of heterogeneous and multi-level omics datasets, which require specific and sometimes complex analyses to obtain relevant biological information. Here, we present ASTERICS (version 2.5), a publicly available web interface for the analyses of omics datasets., Results: ASTERICS is designed to make both standard and complex exploratory and integration analysis workflows easily available to biologists and to provide high quality interactive plots. Special care has been taken to provide a comprehensive documentation of the implemented analyses and to guide users toward sound analysis choices regarding some specific omics data. Data and analyses are organized in a comprehensive graphical workflow within ASTERICS workspace to facilitate the understanding of successive data editions and analyses leading to a given result., Conclusion: ASTERICS provides an easy to use platform for omics data exploration and integration. The modular organization of its open source code makes it easy to incorporate new workflows and analyses by external contributors. ASTERICS is available at https://asterics.miat.inrae.fr and can also be deployed using provided docker images., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Kernel methods have been proven to be a powerful tool for the integration and analysis of high-throughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The kernelized version of principal component analysis is a valid nonlinear alternative to tackle the nonlinearity of biological sample spaces. This paper proposes a novel methodology to obtain a data-driven feature importance based on the kernel PCA representation of the data., Results: The proposed method, kernel PCA Interpretable Gradient (KPCA-IG), provides a data-driven feature importance that is computationally fast and based solely on linear algebra calculations. It has been compared with existing methods on three benchmark datasets. The accuracy obtained using KPCA-IG selected features is equal to or greater than the other methods' average. Also, the computational complexity required demonstrates the high efficiency of the method. An exhaustive literature search has been conducted on the selected genes from a publicly available Hepatocellular carcinoma dataset to validate the retained features from a biological point of view. The results once again remark on the appropriateness of the computed ranking., Conclusions: The black-box nature of kernel PCA needs new methods to interpret the original features. Our proposed methodology KPCA-IG proved to be a valid alternative to select influential variables in high-dimensional high-throughput datasets, potentially unravelling new biological and medical biomarkers., (© 2023. The Author(s).)

Whether in real or simulated microgravity, Humans or animals, the kinetics of cardiovascular adaptation and its regulation by the autonomic nervous system (ANS) remain controversial. In this study, we used hindlimb unloading (HU) in 10 conscious mice. Blood pressure (BP), heart rate (HR), temperature, and locomotor activity were continuously monitored with radio-telemetry, during 3 days of control, 5 days of HU, and 2 days of recovery. Six additional mice were used to assess core temperature. ANS activity was indirectly determined by analyzing both heart rate variability (HRV) and baroreflex sensitivity (BRS). Our study showed that HU induced an initial bradycardia, accompanied by an increase in vagal activity markers of HRV and BRS, together with a decrease in water intake, indicating the early adaptation to fluid redistribution. During HU, BRS was reduced; temperature and BP circadian rhythms were altered, showing a loss in day/night differences, a decrease in cycle amplitude, a drop in core body temperature, and an increase in day BP suggestive of a rise in sympathetic activity. Reloading induced resting tachycardia and a decrease in BP, vagal activity, and BRS. In addition to cardiovascular deconditioning, HU induces disruption in day/night rhythmicity of locomotor activity, temperature, and BP.

This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. In 645 twins (cases = 42%), we trained single- and integrative multi-omics models to identify biomarkers for subclinical aggression and investigated the connections among these biomarkers. Our data comprised transmitted and two non-transmitted polygenic scores (PGSs) for 15 traits, 78,772 CpGs, and 90 metabolites. The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics model comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy for these models in the test (N = 277, cases = 42%) and independent clinical data (N = 142, cases = 45%) ranged from 43 to 57%. We observed strong connections between DNA methylation, amino acids, and parental non-transmitted PGSs for ADHD, Autism Spectrum Disorder, intelligence, smoking initiation, and self-reported health. Aggression-related omics traits link to known and novel risk factors, including inflammation, carcinogens, and smoking., (© 2022. The Author(s).)

In the biomedical field, degradable chemically crosslinked elastomers are interesting materials for tissue engineering applications, since they present rubber-like mechanical properties matching those of soft tissues and are able to preserve their three-dimensional (3D) structure over degradation. Their use in biomedical applications requires surgical handling and implantation that can be a source of accidental damages responsible for the loss of properties. Therefore, their inability to be healed after damage or breaking can be a major drawback. In this work, biodegradable dual-crosslinked networks that exhibit fast and efficient self-healing properties at 37 °C are designed. Self-healable dual-crosslinked (chemically and physically) elastomeric networks are prepared by two methods. The first approach is based on the mix of hydrophobic poly(ethylene glycol)-poly(lactic acid) (PEG-PLA) star-shaped copolymers functionalized with either catechol or methacrylate moieties. In the second approach, hydrophobic bifunctional PEG-PLA star-shaped copolymers with both catechol and methacrylate on their structure are used. In the two systems, the supramolecular network is responsible for the self-healing properties, thanks to the dynamic dissociation/reassociation of the numerous hydrogen bonds between the catechol groups, whereas the covalent network ensures mechanical properties similar to pure methacrylate networks. The self-healable materials display mechanical properties that are compatible with soft tissues and exhibit linear degradation because of the chemical cross-links. The performances of networks from mixed copolymers versus bifunctional copolymers are compared and demonstrate the superiority of the latter. The biocompatibility of the materials is also demonstrated, confirming the potential of these degradable and self-healable elastomeric networks to be used for the design of temporary medical devices.

The high-dimensional nature of proteomics data presents challenges for statistical analysis and biological interpretation. Multivariate analysis, combined with insightful visualization can help to reveal the underlying patterns in complex biological data. This chapter introduces the R package mixOmics which focuses on data exploration and integration. We first introduce methods for single data sets: both Principal Component Analysis, which can identify the patterns of variance present in data, and sparse Partial Least Squares Discriminant Analysis, which aims to identify variables that can classify samples into known groups. We then present integrative methods with Projection to Latent Structures and further extensions for discriminant analysis. We illustrate each technique on a breast cancer multi-omics study and provide the R code and data as online supplementary material for readers interested in reproducing these analyses., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In order to answer new biological questions, high-throughput data generated by new biotechnologies can be very meaningful but require specific and adapted statistical treatments. Thus, in the context of abiotic stress signaling studies, understanding the integration of cascading mechanisms from stress perception to biochemical and physiological adjustments necessarily entails efficient and valid analysis of multilevel and heterogeneous data. In this chapter, we propose examples to manage, analyze, and integrate multi-omics heterogeneous data. This workflow suggests and follows different general biological questions or issues answered with detailed code, data analysis, multiple visualizations, and always followed by brief interpretations. We illustrated this using the mixOmics package for the R software, as it specifically provides tools to address vertical and horizontal data integration issues. In order to illustrate this workflow, we used the usual omics datasets biologists can generate (phenomics, metabolomics, proteomics, and transcriptomics). These data were collected from two organs (leaf rosettes, floral stems) of five ecotypes of the model plant Arabidopsis thaliana exposed to two temperature growth conditions. They are available in the R package WallOmicsData. The workflow presented here is not limited to Arabidopsis thaliana and can be applied to any plant species. It can even be largely deployed to whatever the organisms of interest and the biological questions may be., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In the biomedical field, self-rolling materials provide interesting opportunities to develop medical devices suitable for drug or cell encapsulation. However, to date, a major limitation for medical applications is the use of non-biodegradable and non-biocompatible polymers that are often reported for such applications or the slow actuation witnessed with degradable systems. In this work, biodegradable self-rolling tubes that exhibit a spontaneous and rapid actuation when immersed in water are designed. Photo-crosslinkable hydrophilic and hydrophobic poly(ethylene glycol)-poly(lactide) (PEG-PLA) star-shaped copolymers are prepared and used to prepare bilayered constructs. Thanks to the discrete mechanical and swelling properties of each layer and the cohesive/gradual nature of the interface, the resulting bilayered films are able to self-roll in water in less than 30 s depending on the nature of the hydrophilic layer and on the shape of the sample. The cytocompatibility and degradability of the materials are demonstrated and confirm the potential of such self-rolling resorbable biomaterials in the field of temporary medical devices.

Human expansion in space is hampered by the physiological risks of spaceflight. The muscle and the liver are among the most affected tissues during spaceflight and their relationships in response to space exposure have never been studied. We compared the transcriptome response of liver and quadriceps from mice on NASA RR1 mission, after 37 days of exposure to spaceflight using GSEA, ORA, and sparse partial least square-differential analysis. We found that lipid metabolism is the most affected biological process between the two organs. A specific gene cluster expression pattern in the liver strongly correlated with glucose sparing and an energy-saving response affecting high energy demand process gene expression such as DNA repair, autophagy, and translation in the muscle. Our results show that impaired lipid metabolism gene expression in the liver and muscle atrophy gene expression are two paired events during spaceflight, for which dietary changes represent a possible countermeasure., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)

Essential fatty acids (EFA) and conjugated linoleic acids (CLA) are unsaturated fatty acids with immune-modulatory effects, yet their synergistic effect is poorly understood in dairy cows. This study aimed at identifying differentially abundant proteins (DAP) and their associated pathways in dairy cows supplied with a combination of EFA and CLA during the transition from antepartum (AP) to early postpartum (PP). Sixteen Holstein cows were abomasally infused with coconut oil as a control (CTRL) or a mixture of EFA (linseed + safflower oil) and CLA (Lutalin, BASF) (EFA + CLA) from - 63 to + 63 days relative to parturition. Label-free quantitative proteomics was performed on plasma samples collected at days - 21, + 1, + 28, and + 63. During the transition time, DAP, consisting of a cluster of apolipoproteins (APO), including APOE, APOH, and APOB, along with a cluster of immune-related proteins, were related to complement and coagulation cascades, inflammatory response, and cholesterol metabolism. In response to EFA + CLA, specific APO comprising APOC3, APOA1, APOA4, and APOC4 were increased in a time-dependent manner; they were linked to triglyceride-enriched lipoprotein metabolisms and immune function. Altogether, these results provide new insights into metabolic and immune adaptation and crosstalk between them in transition dairy cows divergent in EFA + CLA status., (© 2022. The Author(s).)

Repeated measurements analysis of variance - simultaneous component analysis (ASCA) has been developed to handle complex longitudinal omics datasets and combine novel information with existing data. Herein, we aimed at applying ASCA to 64 liver proteomes collected at 4-time points (day -21, +1, +28, and + 63 relative to parturition) from 16 Holstein cows treated from 9 wk. antepartum to 9 wk. postpartum (PP) with coconut oil (CTRL) or a mixture of essential fatty acids (EFA) and conjugated linoleic acid (CLA) (EFA + CLA). The ASCA modeled 116, 43, and 97 differentially abundant proteins (DAP) during the transition to lactation, between CTRL and EFA + CLA, and their interaction, respectively. Time-dependent DAP were annotated to pathways related to the metabolism of carbohydrates, FA, and amino acid in the PP period. The DAP between FA and the interaction effect were annotated to the metabolism of xenobiotics by cytochrome P450, drug metabolism - cytochrome P450, retinol metabolism, and steroid hormone biosynthesis. Collectively, ASCA provided novel information on molecular markers of metabolic adaptations and their interactions with EFA + CLA supplementation. Bioinformatics analysis suggested that supplemental EFA + CLA amplified hepatic FA oxidation; cytochrome P450 was enriched to maintain metabolic homeostasis by oxidation/detoxification of endogenous compounds and xenobiotics. SIGNIFICANCE: This report is among the first ones applying repeated measurement analysis of variance-simultaneous component analysis (ASCA) to deal with longitudinal proteomics results. ASCA separately identified differentially abundant proteins (DAP) in 'transition time', 'between fatty acid treatments', and 'their interaction'. We first identified the molecular signature of hepatic metabolic adaptations during postpartum negative energy balance; the enriched pathways were well-known pathways related to mobilizing fatty acids (FA) and amino acids to support continuous energy production through fatty acid oxidation, TCA cycle, and gluconeogenesis. Some of the DAP were not previously reported in transition dairy cows. Secondly, we provide novel information on the mechanisms by which supplemented essential FA and conjugated linoleic acids interact with hepatic metabolism. In this regard, FA amplified hepatic detoxifying and oxidation capacity through ligand activation of nuclear receptors. Finally, we briefly compared the strengths and weaknesses of the ASCA model with PLS-DA and outlined why these methods are complementary., (Copyright © 2021. Published by Elsevier B.V.)

Characterization of the molecular mechanisms involved in tumor cell clustering could open the way to new therapeutic strategies. Towards this aim, we used an in vitro quantitative procedure to monitor the anchorage-independent cell aggregation kinetics in a panel of 25 cancer cell lines. The analysis of the relationship between selected aggregation dynamic parameters and the gene expression data for these cell lines from the CCLE database allowed identifying genes with expression significantly associated with aggregation parameter variations. Comparison of these transcripts with the perturbagen signatures from the Connectivity Map resource highlighted that they were strongly correlated with the transcriptional signature of most histone deacetylase (HDAC) inhibitors. Experimental evaluation of two HDAC inhibitors (SAHA and ISOX) showed that they inhibited the initial step of in vitro tumor cell aggregation. This validates our findings and reinforces the potential interest of HDCA inhibitors to prevent metastasis spreading.

Mycobacterium tuberculosis, the main causative agent of human tuberculosis, is transmitted from person to person via small droplets containing very few bacteria. Optimizing the chance to seed in the lungs is therefore a major adaptation to favor survival and dissemination in the human population. Here we used TnSeq to identify genes important for the early events leading to bacterial seeding in the lungs. Beside several genes encoding known virulence factors, we found three new candidates not previously described: rv0180c, rv1779c and rv1592c. We focused on the gene, rv0180c, of unknown function. First, we found that deletion of rv0180c in M. tuberculosis substantially reduced the initiation of infection in the lungs of mice. Next, we established that Rv0180c enhances entry into macrophages through the use of complement-receptor 3 (CR3), a major phagocytic receptor for M. tuberculosis. Silencing CR3 or blocking the CR3 lectin site abolished the difference in entry between the wild-type parental strain and the Δrv0180c::km mutant. However, we detected no difference in the production of both CR3-known carbohydrate ligands (glucan, arabinomannan, mannan), CR3-modulating lipids (phthiocerol dimycocerosate), or proteins in the capsule of the Δrv0180c::km mutant in comparison to the wild-type or complemented strains. By contrast, we established that Rv0180c contributes to the functionality of the bacterial cell envelope regarding resistance to toxic molecule attack and cell shape. This alteration of bacterial shape could impair the engagement of membrane receptors that M. tuberculosis uses to invade host cells, and open a new perspective on the modulation of bacterial infectivity., Competing Interests: The authors have declared that no competing interests exist.

Electrospun scaffolds combine suitable structural characteristics that make them strong candidates for their use in tissue engineering. These features can be tailored to optimize other physiologically relevant attributes (e.g. mechanical anisotropy and cellular affinity) while ensuring adequate degradation rates of the biomaterial. Here, we present the fabrication of microstructured scaffolds by using a combination of micropatterned electrospinning collectors (honeycomb- or square-patterned) and poly(lactic acid) (PLA)-based copolymers (linear or star-shaped). The resulting materials showed appropriate macropore size and fiber alignment that were key parameters to enhance their anisotropic properties in protraction. Moreover, their elastic modulus, which was initially similar to that of soft tissues, gradually changed in hydrolytic conditions, matching the degradation profile in a 2- to 3-month period. Finally, honeycomb-structured scaffolds exhibited enhanced cellular proliferation compared to standard electrospun mats, while cell colonization was shown to be guided by the macropore contour. Taking together, these results provide new insight into the rational design of microstructured materials that can mimic the progressive evolution of properties in soft tissue regeneration., (Copyright © 2021 Elsevier B.V. All rights reserved.)

High-throughput data generated by new biotechnologies require specific and adapted statistical treatment in order to be efficiently used in biological studies. In this article, we propose a powerful framework to manage and analyse multi-omics heterogeneous data to carry out an integrative analysis. We have illustrated this using the mixOmics package for R software as it specifically addresses data integration issues. Our work also aims at applying the most recent functionalities of mixOmics to real datasets. Although multi-block integrative methodologies exist, we hope to encourage a more widespread use of such approaches in an operational framework by biologists. We have used natural populations of the model plant Arabidopsis thaliana in this work, but the framework proposed is not limited to this plant and can be deployed whatever the organisms of interest and the biological question may be. Four omics datasets (phenomics, metabolomics, cell wall proteomics and transcriptomics) were collected, analysed and integrated to study the cell wall plasticity of plants exposed to sub-optimal temperature growth conditions. The methodologies presented here start from basic univariate statistics leading to multi-block integration analysis. We have also highlighted the fact that each method, either unsupervised or supervised, is associated with one biological issue. Using this powerful framework enabled us to arrive at novel conclusions on the biological system, which would not have been possible using standard statistical approaches., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Anaerobic digestion (AD) is a process that can efficiently degrade organic waste into renewable energies. AD failure is however common as the underpinning microbial mechanisms are highly vulnerable to a wide range of inhibitory compounds. Sequencing technologies enable the identification of microbial indicators of digesters inhibition, but existing studies are limited. They used different inocula, substrates, sites and types of reactors and reported different or contradictory indicators. Our aim was to identify a robust signature of microbial indicators of phenol and ammonia inhibitions across four independent AD microbial studies. To identify such signature, we applied an original multivariate integrative method on two in-house studies, then validated our approach by predicting the inhibitory status of samples from two other studies with more than 90% accuracy. Our approach shows how we can efficiently leverage on existing studies to extract reproducible microbial community patterns and predict AD inhibition to improve AD microbial management., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

In the global warming context, plant adaptation occurs, but the underlying molecular mechanisms are poorly described. Studying natural variation of the model plant Arabidopsis thaliana adapted to various environments along an altitudinal gradient should contribute to the identification of new traits related to adaptation to contrasted growth conditions. The study was focused on the cell wall (CW) which plays major roles in the response to environmental changes. Rosettes and floral stems of four newly-described populations collected at different altitudinal levels in the Pyrenees Mountains were studied in laboratory conditions at two growth temperatures (22 vs. 15 °C) and compared to the well-described Col ecotype. Multi-omic analyses combining phenomics, metabolomics, CW proteomics, and transcriptomics were carried out to perform an integrative study to understand the mechanisms of plant adaptation to contrasted growth temperature. Different developmental responses of rosettes and floral stems were observed, especially at the CW level. In addition, specific population responses are shown in relation with their environment and their genetics. Candidate genes or proteins playing roles in the CW dynamics were identified and will deserve functional validation. Using a powerful framework of data integration has led to conclusions that could not have been reached using standard statistical approaches.

Atrial natriuretic peptide (ANP) is a cardiac hormone controlling blood volume and pressure in mammals. It is still unclear whether ANP controls cold-induced thermogenesis in vivo. Here, we show that acute cold exposure induces cardiac ANP secretion in mice and humans. Genetic inactivation of ANP promotes cold intolerance and suppresses half of cold-induced brown adipose tissue (BAT) activation in mice. While white adipocytes are resistant to ANP-mediated lipolysis at thermoneutral temperature in mice, cold exposure renders white adipocytes fully responsive to ANP to activate lipolysis and a thermogenic program, a physiological response that is dramatically suppressed in ANP null mice. ANP deficiency also blunts liver triglycerides and glycogen metabolism, thus impairing fuel availability for BAT thermogenesis. ANP directly increases mitochondrial uncoupling and thermogenic gene expression in human white and brown adipocytes. Together, these results indicate that ANP is a major physiological trigger of BAT thermogenesis upon cold exposure in mammals., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Cognitive impairment is the most common neurological manifestation in NF1 and occurs in 30-70% of NF1 cases. The onset and severity of each specific cognitive deficit varies greatly from child to child, with no apparent external causes. The wide variability of phenotype is the most complex aspect in terms of management and care. Despite multiple research, the mechanism underlying the high heterogeneity in NF1 has not yet been elucidated. While many studies have focused on the effects of specific and precise genetic mutations on the NF1 phenotype, little has been done on the impact of NF1 transmission (sporadic vs. familial cases). We used a complete neuropsychological evaluation designed to assess five large cognitive areas: general cognitive functions (WISC-IV and EVIP); reading skills (" L'Alouette ," ODEDYS-2 and Lobrot French reading tests); phonological process (ODEDYS-2 test); visual perceptual skills (JLO, Thurstone and Corsi block tests) and attention (CPT-II), as well as psychosocial adjustments (CBCL) to explore the impact of NF1 transmission on cognitive disease manifestation in 96 children affected by NF1 [55 sporadic cases (29♀, 26♂); 41 familial cases (24♀, 17♂)]. Results: Familial and Sporadic form of NF1 only differ in IQ expression. The families' socioeconomic status (SES) impacts IQ performance but not differently between sporadic and familial variants. However, SES is lower in familial variants than in the sporadic variant of NF1. No other cognitive differences emerge between sporadic and familial NF1. Conclusions: Inheritance in NF1 failed to explain the phenotype variability in its entirety. IQ differences between groups seems in part linked to the environment where the child grows up. Children with NF1, and especially those that have early diagnoses (most often in inherited cases), must obtain careful monitoring from their early childhood, at home to strengthen investment in education and in school to early detect emerging academic problems and to quickly place them into care. Trial Registration: IDRCB, IDRCB2008-A01444-51. Registered 19 January 2009., (Copyright © 2020 Biotteau, Déjean, Lelong, Iannuzzi, Faure-Marie, Castelnau, Rivier, Lauwers-Cancès, Baudou and Chaix.)

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins ( N = 1,347) and clinic-referred children ( N = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression ( N = 783); a replication phase in twin pairs discordant for aggression ( N = 378); and a validation phase in clinical cases and matched twin controls ( N = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine (β = 0.36; SE = 0.09; p = 0.004), and gamma-L-glutamyl-L-alanine (β = 0.32; SE = 0.09; p = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression., (Copyright © 2020 Hagenbeek, Roetman, Pool, Kluft, Harms, van Dongen, Colins, Talens, van Beijsterveldt, Vandenbosch, de Zeeuw, Déjean, Fanos, Ehli, Davies, Hottenga, Hankemeier, Bartels, Vermeiren and Boomsma.)

Foot and mouth disease (FMD) is a highly contagious viral disease with high economic impact, representing a major threat for cloven-hooved mammals worldwide. Vaccines based on adjuvanted inactivated virus (iFMDV) induce effective protective immunity implicating antibody (Ab) responses. To reduce the biosafety constraints of the manufacturing process, a non-replicative human adenovirus type 5 vector encoding FMDV antigens (Ad5-FMDV) has been developed. Here we compared the immunogenicity of iFMDV and Ad5-FMDV with and without the ISA206VG emulsion-type adjuvant in sheep. Contrasted Ab responses were obtained: iFMDV induced the highest Ab levels, Ad5-FMDV the lowest ones, and ISA206VG increased the Ad5-FMDV-induced Ab responses to protective levels. Each vaccine generated heterogeneous Ab responses, with high and low responders, the latter being considered as obstacles to vaccine effectiveness. A transcriptomic study on total blood responses at 24 h post-vaccination revealed several blood gene module activities correlating with long-term Ab responses. Downmodulation of T cell modules' activities correlated with high responses to iFMDV and to Ad5-FMDV+ISA206VG vaccines as also found in other systems vaccinology studies in humans and sheep. The impact of cell cycle activity depended on the vaccine types, as it positively correlated with higher responses to iFMDV but negatively to non-adjuvanted Ad5-FMDV. Finally an elevated B cell activity at 24 h correlated with high Ab responses to the Ad5-FMDV+ISA206VG vaccine. This study provides insights into the early mechanisms driving the Ab response induced by different vaccine regimens including Ad5 vectors and points to T cell modules as early biomarker candidates of different vaccine-type efficacy across species., Competing Interests: Competing interestsN.V. is employed by SEPPIC. P.H. and M.C. are employed by Merial-Boehringer Ingelheim. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The other authors declare no competing interest., (© The Author(s) 2020.)

Macroecologists seek to identify drivers of community turnover ( β -diversity) through broad spatial scales. However, the influence of local habitat features in driving broad-scale β -diversity patterns remains largely untested, owing to the objective challenges of associating local-scale variables to continental-framed datasets. We examined the relative contribution of local- versus broad-scale drivers of continental β -diversity patterns, using a uniquely suited dataset of cave-dwelling spider communities across Europe (35-70° latitude). Generalized dissimilarity modelling showed that geographical distance, mean annual temperature and size of the karst area in which caves occurred drove most of β -diversity, with differential contributions of each factor according to the level of subterranean specialization. Highly specialized communities were mostly influenced by geographical distance, while less specialized communities were mostly driven by mean annual temperature. Conversely, local-scale habitat features turned out to be meaningless predictors of community change, which emphasizes the idea of caves as the human accessible fraction of the extended network of fissures that more properly represents the elective habitat of the subterranean fauna. To the extent that the effect of local features turned to be inconspicuous, caves emerge as experimental model systems in which to study broad biological patterns without the confounding effect of local habitat features.

Background: Spiders (Arachnida: Araneae) are widespread in subterranean ecosystems worldwide and represent an important component of subterranean trophic webs. Yet, global-scale diversity patterns of subterranean spiders are still mostly unknown. In the frame of the CAWEB project, a European joint network of cave arachnologists, we collected data on cave-dwelling spider communities across Europe in order to explore their continental diversity patterns. Two main datasets were compiled: one listing all subterranean spider species recorded in numerous subterranean localities across Europe and another with high resolution data about the subterranean habitat in which they were collected. From these two datasets, we further generated a third dataset with individual geo-referenced occurrence records for all these species., New Information: Data from 475 geo-referenced subterranean localities (caves, mines and other artificial subterranean sites, interstitial habitats) are herein made available. For each subterranean locality, information about the composition of the spider community is provided, along with local geomorphological and habitat features. Altogether, these communities account for > 300 unique taxonomic entities and 2,091 unique geo-referenced occurrence records, that are made available via the Global Biodiversity Information Facility (GBIF) (Mammola and Cardoso 2019). This dataset is unique in that it covers both a large geographic extent (from 35° south to 67° north) and contains high-resolution local data on geomorphological and habitat features. Given that this kind of high-resolution data are rarely associated with broad-scale datasets used in macroecology, this dataset has high potential for helping researchers in tackling a range of biogeographical and macroecological questions, not necessarily uniquely related to arachnology or subterranean biology., (Stefano Mammola, Pedro Cardoso, Dorottya Angyal, Gergely Balázs, Theo Blick, Hervé Brustel, Julian Carter, Srećko Ćurčić, Samuel Danflous, László Dányi, Sylvain Déjean, Christo Deltshev, Mert Elverici, Jon Fernández, Fulvio Gasparo, Marjan Komnenov, Christian Komposch, L’ubomír Kováč, Kadir Boğaç Kunt, Andrej Mock, Oana Moldovan, Maria Naumova, Martina Pavlek, Carlos E. Prieto, Carles Ribera, Robert Rozwałka, Vlastimil Růžička, Robert S. Vargovitsh, Stefan Zaenker, Marco Isaia.)

Albumins and globulins (AGs) of wheat endosperm represent about 20% of total grain proteins. Some of these physiologically active proteins can influence the synthesis of storage proteins (SPs) (gliadins and glutenins) and consequently, rheological properties of wheat flour and processing. To identify such AGs, data, (published by Bonnot et al., 2017) concerning abundance in 352 AGs and in the different seed SPs during grain filling and in response to different nitrogen (N) and sulfur (S) supply, were integrated with mixOmics R package. Relationships between AGs and SPs were first unraveled using the unsupervised method sparse Partial Least Square, also known as Projection to Latent Structure (sPLS). Then, data were integrated using a supervised approach taking into account the nutrition and the grain developmental stage. We used the block.splda procedure also referred to as DIABLO (Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies). These approaches led to the identification of discriminant and highly correlated features from the two datasets (AGs and SPs) which are not necessarily differentially expressed during seed development or in response to N or S supply. Eighteen AGs were correlated with the quantity of SPs per grain. A statistical validation of these proteins by genetic association analysis confirmed that 5 out of this AG set were robust candidate proteins able to modulate the seed SP synthesis. In conclusion, this latter result confirmed that the integrative strategy is an adequate way to reduce the number of potentially relevant AGs for further functional validation.

Natural variations help in identifying genetic mechanisms of morphologically and developmentally complex traits. Mountainous habitats provide an altitudinal gradient where one species encounters different abiotic conditions. We report the study of 341 individuals of Arabidopsis thaliana derived from 30 natural populations not belonging to the 1001 genomes, collected at increasing altitudes, between 200 and 1800 m in the Pyrenees. Class III peroxidases and ribosomal RNA sequences were used as markers to determine the putative genetic relationships among these populations along their altitudinal gradient. Using Bayesian-based statistics and phylogenetic analyses, these Pyrenean populations appear with significant divergence from the other regional accessions from 1001 genome (i.e., from north Spain or south France). Individuals of these populations exhibited varying phenotypic changes, when grown at sub-optimal temperature (22 vs. 15°C). These phenotypic variations under controlled conditions reflected intraspecific morphological variations. This study could bring new information regarding the west European population structure of A. thaliana and its phenotypic variations at different temperatures. The integrative analysis combining genetic, phenotypic variation and environmental datasets is used to analyze the acclimation of population in response to temperature changes. Regarding their geographical proximity and environmental diversity, these populations represent a tool of choice for studying plant response to temperature variation., Highlights: -Studying the natural diversity of A. thaliana in the Pyrenees mountains helps to understand European population structure and to evaluate the phenotypic trait variation in response to climate change.