Human Milk Oligosaccharides in Maternal Serum Respond to Oral Glucose Load and Are Associated with Insulin Sensitivity.

(1) Background: Pregnancy presents a challenge to maternal glucose homeostasis; suboptimal adaptations can lead to gestational diabetes mellitus (GDM). Human milk oligosaccharides (HMOs) circulate in maternal blood in pregnancy and are altered with GDM, suggesting influence of glucose homeostasis on HMOs. We thus assessed the HMO response to glucose load during an oral glucose tolerance test (OGTT) and investigated HMO associations with glucose tolerance/insulin sensitivity in healthy pregnant women. (2) Methods: Serum of 99 women, collected at 0 h, 1 h and 2 h during a 75 g OGTT at 24-28 gestational weeks was analyzed for HMOs (2'FL, 3'SLN, LDFT, 3'SL) by HPLC; plasma glucose, insulin and C-peptide were analyzed by standard biochemistry methods. (3) Results: Serum 3'SL concentrations significantly increased from fasting to 1 h after glucose load, while concentrations of the other HMOs were unaltered. Higher 3'SL at all OGTT time points was associated with a generally more diabetogenic profile, with higher hepatic insulin resistance (HOMA-IR), lower insulin sensitivity (Matsuda index) and higher insulin secretion (C-peptide index 1). (4) Conclusions: Rapid increase in serum 3'SL post-oral glucose load (fasted-fed transition) indicates utilization of plasma glucose, potentially for sialylation of lactose. Associations of sialylated HMOs with a more diabetogenic profile suggest sustained adaptations to impaired glucose homeostasis in pregnancy. Underlying mechanisms or potential consequences of observed HMO changes remain to be elucidated.

["Old'up": creative aging...] / Old'up, un vieillissement créatif.

The association Old'up, which is celebrating its 11th anniversary, was created by the Ecole des grands-parents européens. It is an avant-garde witness to the effects of lengthening life. Founded by old people, for old people, with old people, even very old people, the association want to be the voice of this population which has been growing so fast for fifteen years.

Reduced Resting-State Connectivity in the Precuneus is correlated with Apathy in Patients with Schizophrenia.

A diagnosis of schizophrenia is associated with a heterogeneous psychopathology including positive and negative symptoms. The disconnection hypothesis, an early pathophysiological framework conceptualizes the diversity of symptoms as a result of disconnections in neural networks. In line with this hypothesis, previous neuroimaging studies of patients with schizophrenia reported alterations within the default mode network (DMN), the most prominent network at rest. The aim of the present study was to investigate the functional connectivity during rest in patients with schizophrenia and with healthy individuals and explore whether observed functional alterations are related to the psychopathology of patients. Therefore, functional magnetic resonance images at rest were recorded of 35 patients with schizophrenia and 41 healthy individuals. Independent component analysis (ICA) was used to extract resting state networks. Comparing ICA results between groups indicated alterations only within the network of the DMN. More explicitly, reduced connectivity in the precuneus was observed in patients with schizophrenia compared to healthy controls. Connectivity in this area was negatively correlated with the severity of negative symptoms, more specifically with the domain of apathy. Taken together, the current results provide further evidence for a role DMN alterations might play in schizophrenia and especially in negative symptoms such as apathy.

New Graph-Theoretical-Multimodal Approach Using Temporal and Structural Correlations Reveals Disruption in the Thalamo-Cortical Network in Patients with Schizophrenia.

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive, and behavioral symptoms in this disorder. When building brain networks, functional and structural networks are typically modeled independently: Functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks. In this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural, and topological information of magnetic resonance imaging (MRI) measurements (structural and resting-state imaging) to patients with schizophrenia (n = 35) and matched healthy individuals (n = 41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out. By using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole-brain connectivity, including functional, structural, and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity, resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting-state functional MRI, and it can be applied to electro-encephalography, magneto-encephalography, etc.