Investigating prenatal perceived support as protective factor against adverse birth outcomes: a community cohort study.

Studies show that prenatal maternal anxiety may act as a risk factor for adverse birth outcomes, whilst prenatal social support may rather act as a protective factor. However, studies examining prenatal anxiety symptoms, prenatal perceived support, and neonatal and/or obstetric outcomes are lacking. This study investigated whether, in a community sample, prenatal perceived support: (1) had a protective influence on birth outcomes (gestational age (GA), birthweight (BW), 5-minute Apgar score, and mode of delivery); (2) acted as a protective factor, moderating the relationship between anxiety symptoms and the aforementioned birth outcomes. During their third trimester of pregnancy, 182 nulliparous child-bearers completed standardized questionnaires of anxiety (HADS-A) and perceived support (MOS-SSS). Birth outcomes data was extracted from medical records. (1) Perceived support did not significantly predict any birth outcomes. However, perceived tangible support - MOS-SSS subscale assessing perceived material/financial aid - significantly positively predicted the 5-minute Apgar score. (2) Perceived support did not significantly moderate the relationship between anxiety symptoms and birth outcomes. However, perceived tangible support significantly moderated the relationship between anxiety symptoms and the 5-minute Apgar score. When experienced within non-clinical thresholds, prenatal anxiety symptoms do not increase the risk of adverse neonatal and obstetric outcomes when perceived support is present

Effects of confinement and crowding on folding of model proteins

We perform molecular dynamics simulations for a simple coarse-grained model of crambin placed inside of a softly repulsive sphere of radius R. The confinement makes folding at the optimal temperature slower and affects the folding scenarios, but both effects are not dramatic. The influence of crowding on folding are studied by placing several identical proteins within the sphere, denaturing them, and then by monitoring refolding. If the interactions between the proteins are dominated by the excluded volume effects, the net folding times are essentially like for a single protein. An introduction of inter-proteinic attractive contacts hinders folding when the strength of the attraction exceeds about a half of the value of the strength of the single protein contacts. The bigger the strength of the attraction, the more likely is the occurrence of aggregation and misfolding

Adenosine A1-A2A receptor-receptor interaction: contribution to guanosine-mediated effects

Guanosine, a guanine-based purine nucleoside, has been described as a neuromodulator that exerts neuroprotective effects in animal and cellular ischemia models. However, guanosine's exact mechanism of action and molecular targets have not yet been identified. Here, we aimed to elucidate a role of adenosine receptors (ARs) in mediating guanosine effects. We investigated the neuroprotective effects of guanosine in hippocampal slices from A2AR-deficient mice (A2AR-/-) subjected to oxygen/glucose deprivation (OGD). Next, we assessed guanosine binding at ARs taking advantage of a fluorescent-selective A2AR antagonist (MRS7396) which could engage in a bioluminescence resonance energy transfer (BRET) process with NanoLuc-tagged A2AR. Next, we evaluated functional AR activation by determining cAMP and calcium accumulation. Finally, we assessed the impact of A1R and A2AR co-expression in guanosine-mediated impedance responses in living cells. Guanosine prevented the reduction of cellular viability and increased reactive oxygen species generation induced by OGD in hippocampal slices from wild-type, but not from A2AR-/- mice. Notably, while guanosine was not able to modify MRS7396 binding to A2AR-expressing cells, a partial blockade was observed in cells co-expressing A1R and A2AR. The relevance of the A1R and A2AR interaction in guanosine effects was further substantiated by means of functional assays (i.e., cAMP and calcium determinations), since guanosine only blocked A2AR agonist-mediated effects in doubly expressing A1R and A2AR cells. Interestingly, while guanosine did not affect A1R/A2AR heteromer formation, it reduced A2AR agonist-mediated cell impedance responses. Our results indicate that guanosine-induced effects may require both A1R and A2AR co-expression, thus identifying a molecular substrate that may allow fine tuning of guanosine-mediated responses

IMGT/V-QUEST: the highly customized and integrated system for IG and TR standardized V-J and V-D-J sequence analysis

IMGT/V-QUEST is the highly customized and integrated system for the standardized analysis of the immunoglobulin (IG) and T cell receptor (TR) rearranged nucleotide sequences. IMGT/V-QUEST identifies the variable (V), diversity (D) and joining (J) genes and alleles by alignment with the germline IG and TR gene and allele sequences of the IMGT reference directory. New functionalities were added through a complete rewrite in Java. IMGT/V-QUEST analyses batches of sequences (up to 50) in a single run. IMGT/V-QUEST describes the V-REGION mutations and identifies the hot spot positions in the closest germline V gene. IMGT/V-QUEST can detect insertions and deletions in the submitted sequences by reference to the IMGT unique numbering. IMGT/V-QUEST integrates IMGT/JunctionAnalysis for a detailed analysis of the V-J and V-D-J junctions, and IMGT/Automat for a full V-J- and V-D-J-REGION annotation. IMGT/V-QUEST displays, in ‘Detailed view’, the results and alignments for each submitted sequence individually and, in ‘Synthesis view’, the alignments of the sequences that, in a given run, express the same V gene and allele. The ‘Advanced parameters’ allow to modify default parameters used by IMGT/V-QUEST and IMGT/JunctionAnalysis according to the users’ interest. IMGT/V-QUEST is freely available for academic research at http://imgt.cines.f

Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure

peer reviewe

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity.

[en] UNLABELLED: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures. AUTHOR SUMMARY: In recent years, we see the increasing possibility of collecting data from multiple modalities in various fields, requesting novel methods to exploit the consensus among different data types. As exemplified in systems biology or epistasis analyses, the interactions between features may contain more information than the features themselves, thereby necessitating the use of feature networks. Furthermore, in real-life scenarios, subjects, such as patients or individuals, may originate from diverse populations, which underscores the importance of subtyping or clustering these subjects to account for their heterogeneity. In this study, we present a novel pipeline for selecting the most relevant features from multiple data types, constructing a feature network for each subject, and obtaining a subgrouping of samples informed by a phenotype of interest. We validated our method on synthetic data and demonstrated its superiority over several state-of-the-art multi-view clustering approaches. Additionally, we applied our method to a real-life, large-scale dataset of genomic data and facial images, where it effectively identified a meaningful BMI subtyping that complemented existing BMI categories and offered new biological insights. Our proposed method has wide applicability to complex multi-view or multi-omics datasets for tasks such as disease subtyping or personalized medicine

Diabetes-induced mechanical hyperalgesia involves spinal mitogen-activated protein kinase activation in neurons and microglia via N-methyl-D-aspartate-dependent mechanisms

ABSTRACT Molecular mechanisms underlying diabetes-induced painful neuropathy are poorly understood. We have demonstrated, in rats with streptozotocin-induced diabetes, that mechanical hyperalgesia, a common symptom of diabetic neuropathy, was correlated with an early increase in extracellular signal-regulated protein kinase (ERK), p38, and c-Jun N-terminal kinase (JNK) phosphorylation in the spinal cord and dorsal root ganglion at 3 weeks after induction of diabetes. This change was specific to hyperalgesia because nonhyperalgesic rats failed to have such an increase. Immunoblot analysis showed no variation of protein levels, suggesting a post-translational regulation of the corresponding kinases. In diabetic hyperalgesic rats, immunocytochemistry revealed that all phosphorylated mitogen-activated protein kinases (MAPKs) colocalized with both the neuronal (NeuN) and microglial (OX42) cell-specific markers but not with the astrocyte marker [glial fibrillary acidic protein (GFAP)] in the superficial dorsal horn-laminae of the spinal cord. In these same rats, a 7-day administration [5 g/rat/day, intrathecal (i.t.)] of 1,4-diamino-2,3-dicyano-1,4-bis(2-aminophenylthio)butadiene (U0126), 4-(4-fluorophenyl)-2-(4-methylsulfinylphenyl)-5-(4-pyridyl)1H-imidazole (SB203580), and anthra(1,9-cd)pyrazol-6(2H)-one (SP600125), which inhibited MAPK kinase, p38, and JNK, respectively, suppressed mechanical hyperalgesia, and decreased phosphorylation of the kinases. To characterize the cellular events upstream of MAPKs, we have examined the role of the NMDA receptor known to be implicated in pain hypersensitivity. The prolonged blockade of this receptor during 7 days by (5R,10S)-(ϩ)-5-methyl-10, 11-dihydro-5H-dibenzo[a,d]-cyclohepten-5-10-imine hydrogen maleate (MK801; 5 g/rat/day, i.t.), a noncompetitive NMDA receptor antagonist, reversed hyperalgesia developed by diabetic rats and blocked phosphorylation of all MAPKs. These results demonstrate for the first time that NMDA receptor-dependent phosphorylation of MAPKs in spinal cord neurons and microglia contribute to the establishment and longterm maintenance of painful diabetic hyperalgesia and that these kinases represent potential targets for pain therapy. Sensitive peripheral neuropathies represent a common and debilitating complication of diabetes (types 1 and 2) and affect an increasing proportion of diabetic patients as the disease progresses. Even though antidepressant and antiepileptic agents have been shown to be partially effective, clinical studies have reported the difficulty of managing pain caused by these neuropathies The mitogen-activated protein kinase (MAPK) cascade is a family of serine/threonine kinases that are activated by dual phosphorylation on threonine and tyrosine residues. The Article, publication date, and citation information can be found a

IMGT®, the international ImMunoGeneTics information system®

IMGT®, the international ImMunoGeneTics information system® (http://www.imgt.org), was created in 1989 by Marie-Paule Lefranc, Laboratoire d'ImmunoGénétique Moléculaire LIGM (Université Montpellier 2 and CNRS) at Montpellier, France, in order to standardize and manage the complexity of immunogenetics data. The building of a unique ontology, IMGT-ONTOLOGY, has made IMGT® the global reference in immunogenetics and immunoinformatics. IMGT® is a high-quality integrated knowledge resource specialized in the immunoglobulins or antibodies, T cell receptors, major histocompatibility complex, of human and other vertebrate species, proteins of the IgSF and MhcSF, and related proteins of the immune systems of any species. IMGT® provides a common access to standardized data from genome, proteome, genetics and 3D structures. IMGT® consists of five databases (IMGT/LIGM-DB, IMGT/GENE-DB, IMGT/3Dstructure-DB, etc.), fifteen interactive online tools for sequence, genome and 3D structure analysis, and more than 10 000 HTML pages of synthesis and knowledge. IMGT® is used in medical research (autoimmune diseases, infectious diseases, AIDS, leukemias, lymphomas and myelomas), veterinary research, biotechnology related to antibody engineering (phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (clonalities, detection and follow-up of residual diseases) and therapeutical approaches (graft, immunotherapy, vaccinology). IMGT is freely available at http://www.imgt.org