Maternal Western diet programs cardiometabolic dysfunction and hypothalamic inflammation via epigenetic mechanisms predominantly in the male offspring

OBJECTIVE

Maternal exposure during pregnancy is a strong determinant of offspring health outcomes. Such exposure induces changes in the offspring epigenome resulting in gene expression and functional changes. In this study, we investigated the effect of maternal Western hypercaloric diet (HCD) programming during the perinatal period on neuronal plasticity and cardiometabolic health in adult offspring.

METHODS

C57BL/6J dams were fed HCD for 1 month prior to mating with regular diet (RD) sires and kept on the same diet throughout pregnancy and lactation. At weaning, offspring were maintained on either HCD or RD for 3 months resulting in 4 treatment groups that underwent cardiometabolic assessments. DNA and RNA were extracted from the hypothalamus to perform whole genome methylation, mRNA, and miRNA sequencing followed by bioinformatic analyses.

RESULTS

Maternal programming resulted in male-specific hypertension and hyperglycemia, with both males and females showing increased sympathetic tone to the vasculature. Surprisingly, programmed male offspring fed HCD in adulthood exhibited lower glucose levels, less insulin resistance, and leptin levels compared to non-programmed HCD-fed male mice. Hypothalamic genes involved in inflammation and type 2 diabetes were targeted by differentially expressed miRNA, while genes involved in glial and astrocytic differentiation were differentially methylated in programmed male offspring. These data were supported by our findings of astrogliosis, microgliosis and increased microglial activation in programmed males in the paraventricular nucleus (PVN). Programming induced a protective effect in male mice fed HCD in adulthood, resulting in lower protein levels of hypothalamic TGFβ2, NF-κB2, NF-κBp65, Ser-pIRS1, and GLP1R compared to non-programmed HCD-fed males. Although TGFβ2 was upregulated in male mice exposed to HCD pre- or post-natally, only blockade of the brain TGFβ receptor in RD-HCD mice improved glucose tolerance and a trend to weight loss.

CONCLUSIONS

Our study shows that maternal HCD programs neuronal plasticity in the offspring and results in male-specific hypertension and hyperglycemia associated with hypothalamic inflammation in mechanisms and pathways distinct from post-natal HCD exposure. Together, our data unmask a compensatory role of HCD programming, likely via priming of metabolic pathways to handle excess nutrients in a more efficient way.

Efficacy of a hospital policy of selective digestive decontamination for carbapenem-resistant Enterobacterales carriers: prospective before-after study

A single-centre interrupted time series quasi-experimental study was undertaken to assess whether a hospital policy of selective digestive decontamination (SDD, gentamicin/amikacin with neomycin) administered to carbapenem-resistant Enterobacterales (CRE) carriers would reduce the duration of carriage and contain the spread of CRE. No significant difference in time to CRE eradication was observed between the observation (12 months, 120 patients) and intervention (12 months, 101 patients) periods. No change in the trend of new in-hospital CRE acquisitions or bacteraemia during the intervention was detected. As such, administration of SDD to CRE carriers was not effective for the eradication of carriage or controlling in-hospital CRE transmissions.

Deep Learning Approach for Epileptic Focus Localization

The task of epileptic focus localization receives great attention due to its role in an effective epileptic surgery. The clinicians highly depend on the intracranial EEG data to make a surgical decision related to epileptic subjects suffering from uncontrollable seizures. This surgery usually aims to remove the epileptogenic region which requires precise characterization of that area using the EEG recordings. In this paper, we propose two methods based on deep learning targeting accurate automatic epileptic focus localization using the non-stationary EEG recordings. Our first proposed method is based on semi-supervised learning, in which a deep convolutional autoencoder is trained and then the pre-trained encoder is used with multi-layer perceptron as a classifier. The goal is to determine the location of the EEG signal that is responsible for the epileptic activity. In the second proposed method, unsupervised learning scheme is implemented by merging deep convolutional variational autoencoder and K-means algorithm for clustering the iEEG signals into two distinct clusters based on the seizure source. The proposed methods automate and integrate the features extraction and classification processes instead of manually extracting the features as done in the previous studies. Dimensionality reduction is achieved using the autoencoder, while the important spatio-temporal features are extracted from the EEG recordings using the convolutional layers. Moreover, we implemented the inference network of the semi-supervised model on FPGA. The results of our experiments demonstrate high classification accuracy and clustering performance in localizing the epileptic focus compared with the state of the art.

Efficient Epileptic Seizure Prediction Based on Deep Learning

Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patients' life. In this paper, a novel patient-specific seizure prediction technique based on deep learning and applied to long-term scalp electroencephalogram (EEG) recordings is proposed. The goal is to accurately detect the preictal brain state and differentiate it from the prevailing interictal state as early as possible and make it suitable for real time. The features extraction and classification processes are combined into a single automated system. Raw EEG signal without any preprocessing is considered as the input to the system which further reduces the computations. Four deep learning models are proposed to extract the most discriminative features which enhance the classification accuracy and prediction time. The proposed approach takes advantage of the convolutional neural network in extracting the significant spatial features from different scalp positions and the recurrent neural network in expecting the incidence of seizures earlier than the current methods. A semi-supervised approach based on transfer learning technique is introduced to improve the optimization problem. A channel selection algorithm is proposed to select the most relevant EEG channels which makes the proposed system good candidate for real-time usage. An effective test method is utilized to ensure robustness. The achieved highest accuracy of 99.6% and lowest false alarm rate of 0.004 h ^{- 1} along with very early seizure prediction time of 1 h make the proposed method the most efficient among the state of the art.

Phase separation in equiatomic AlCoCrFeNi high-entropy alloy

The microstructure of the as-cast AlCoCrFeNi high entropy alloy has been investigated by transmission electron microscopy and atom probe tomography. The alloy shows a very pronounced microstructure with clearly distinguishable dendrites and interdendrites. In both regions a separation into an Al-Ni rich matrix and Cr-Fe-rich precipitates can be observed. Moreover, fluctuations of single elements within the Cr-Fe rich phase have been singled out by three dimensional atom probe measurements. The results of investigations are discussed in terms of spinodal decomposition of the alloying elements inside the Cr-Fe-rich precipitates.

Mutations in FUS cause FALS and SALS in French and French Canadian populations

BACKGROUND

The identification of mutations in the TARDBP and more recently the identification of mutations in the FUS gene as the cause of amyotrophic lateral sclerosis (ALS) is providing the field with new insight about the mechanisms involved in this severe neurodegenerative disease.

METHODS

To extend these recent genetic reports, we screened the entire gene in a cohort of 200 patients with ALS. An additional 285 patients with sporadic ALS were screened for variants in exon 15 for which mutations were previously reported.

RESULTS

In total, 3 different mutations were identified in 4 different patients, including 1 3-bp deletion in exon 3 of a patient with sporadic ALS and 2 missense mutations in exon 15 of 1 patient with familial ALS and 2 patients with sporadic ALS.

CONCLUSIONS

Our study identified sporadic patients with mutations in the FUS gene. The accumulation and description of different genes and mutations helps to develop a more comprehensive picture of the genetic events underlying amyotrophic lateral sclerosis.

Contribution of TARDBP mutations to sporadic amyotrophic lateral sclerosis

AIMS AND BACKGROUND

Mutations in the TARDBP gene, which encodes the TAR DNA binding protein (TDP-43), have been described in individuals with familial and sporadic amyotrophic lateral sclerosis (ALS). We screened the TARDBP gene in 285 French sporadic ALS patients to assess the frequency of TARDBP mutations in ALS.

RESULTS

Six individuals had potentially deleterious mutations of which three were novel including a Y374X truncating mutation and P363A and A382P missense mutations. This suggests that TARDBP mutations may predispose to ALS in approximately 2% of the individuals followed in this study.

CONCLUSION

Our findings, combined with those from other collections, brings the total number of mutations in unrelated ALS patients to 17, further suggesting that mutations in the TARDBP gene have an important role in the pathogenesis of ALS.

Genetic linkage analysis of schizophrenia using chromosome 11q13-24 markers in Israeli pedigrees

It is generally agreed that there is a genetic component in the etiology of schizophrenia which may be tested by the application of linkage analysis to multiply-affected families. One genetic region of interest is the long arm of chromosome 11 because of previously reported associations of genetic variation in this region with schizophrenia, and because of the fact that it contains the locus for the dopamine D2 receptor gene. In this study we have examined the segregation of schizophrenia with microsatellite dinucleotide repeat DNA markers along chromosome 11q in 5 Israeli families multiply-affected for schizophrenia. The hypothesis of linkage under genetic homogeneity of causation was tested under a number of genetic models. Linkage analysis provided no evidence for significant causal mutations within the region bounded by INT and D11S420 on chromosome 11q. It is still possible, however, that a gene of major effect exists in this region, either with low penetrance or with heterogeneity.

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The well-known reaction between thiols and mercuric salts can be used for determination of the former. The method has been extended to determination of several organomercurials. Cysteine is used for titration of hydroxyaryl mercury compounds. The presence of a chloride or sulphur atom bound to the metal makes the method inapplicable, however.