Wireless monitoring of respiration with EEG reveals relationships between respiration, behaviour and brain activity in freely moving mice.

Active sampling in the olfactory domain is an important aspect of mouse behaviour, and there is increasing evidence that respiration-entrained neural activity outside of the olfactory system sets an important global brain rhythm. It is therefore important to accurately measure breathing during natural behaviours. We develop a new approach to do this in freely moving animals, by implanting a telemetry-based pressure sensor into the right jugular vein, which allows for wireless monitoring of thoracic pressure. After verifying this technique against standard head-fixed respiration measurements, we combined it with EEG and EMG recording and used evolving partial coherence analysis to investigate the relationship between respiration and brain activity across a range of experiments in which the mice could move freely. During voluntary exploration of odours and objects, we found that the association between respiration and cortical delta and theta rhythms decreased, while the association between respiration and cortical alpha rhythm increased. During sleep, however, the presentation of an odour was able to cause a transient increase in sniffing without changing dominant sleep rhythms (delta and theta) in the cortex. Our data align with the emerging idea that the respiration rhythm could act as a synchronising scaffold for specific brain rhythms during wakefulness and exploration, but suggest that respiratory changes are less able to impact brain activity during sleep. Combining wireless respiration monitoring with different types of brain recording across a variety of behaviours will further increase our understanding of the important links between active sampling, passive respiration, and neural activity.

Hormone-mediated neural remodeling orchestrates parenting onset during pregnancy.

During pregnancy, physiological adaptations prepare the female body for the challenges of motherhood. Becoming a parent also requires behavioral adaptations. Such adaptations can occur as early as during pregnancy, but how pregnancy hormones remodel parenting circuits to instruct preparatory behavioral changes remains unknown. We found that action of estradiol and progesterone on galanin (Gal)-expressing neurons in the mouse medial preoptic area (MPOA) is critical for pregnancy-induced parental behavior. Whereas estradiol silences MPOAGal neurons and paradoxically increases their excitability, progesterone permanently rewires this circuit node by promoting dendritic spine formation and recruitment of excitatory synaptic inputs. This MPOAGal-specific neural remodeling sparsens population activity in vivo and results in persistently stronger, more selective responses to pup stimuli. Pregnancy hormones thus remodel parenting circuits in anticipation of future behavioral need.

ALDH1L2 regulation of formate, formyl-methionine, and ROS controls cancer cell migration and metastasis.

Mitochondrial 10-formyltetrahydrofolate (10-formyl-THF) is utilized by three mitochondrial enzymes to produce formate for nucleotide synthesis, NADPH for antioxidant defense, and formyl-methionine (fMet) to initiate mitochondrial mRNA translation. One of these enzymes-aldehyde dehydrogenase 1 family member 2 (ALDH1L2)-produces NADPH by catabolizing 10-formyl-THF into CO2 and THF. Using breast cancer cell lines, we show that reduction of ALDH1L2 expression increases ROS levels and the production of both formate and fMet. Both depletion of ALDH1L2 and direct exposure to formate result in enhanced cancer cell migration that is dependent on the expression of the formyl-peptide receptor (FPR). In various tumor models, increased ALDH1L2 expression lowers formate and fMet accumulation and limits metastatic capacity, while human breast cancer samples show a consistent reduction of ALDH1L2 expression in metastases. Together, our data suggest that loss of ALDH1L2 can support metastatic progression by promoting formate and fMet production, resulting in enhanced FPR-dependent signaling.

Antiretroviral Treatment-Induced Decrease in Immune Activation Contributes to Reduced Susceptibility to Tuberculosis in HIV-1/Mtb Co-infected Persons.

Antiretroviral treatment (ART) reduces the risk of developing active tuberculosis (TB) in HIV-1 co-infected persons. In order to understand host immune responses during ART in the context of Mycobacterium tuberculosis (Mtb) sensitization, we performed RNAseq analysis of whole blood-derived RNA from individuals with latent TB infection coinfected with HIV-1, during the first 6 months of ART. A significant fall in RNA sequence abundance of the Hallmark IFN-alpha, IFN-gamma, IL-6/JAK/STAT3 signaling, and inflammatory response pathway genes indicated reduced immune activation and inflammation at 6 months of ART compared to day 0. Further exploratory evaluation of 65 soluble analytes in plasma confirmed the significant decrease of inflammatory markers after 6 months of ART. Next, we evaluated 30 soluble analytes in QuantiFERON Gold in-tube (QFT) samples from the Ag stimulated and Nil tubes, during the first 6 months of ART in 30 patients. There was a significant decrease in IL-1alpha and IL-1beta (Ag-Nil) concentrations as well as MCP-1 (Nil), supporting decreased immune activation and inflammation. At the same time, IP-10 (Ag-nil) concentrations significantly increased, together with chemokine receptor-expressing CD4 T cell numbers. Our data indicate that ART-induced decrease in immune activation combined with improved antigen responsiveness may contribute to reduced susceptibility to tuberculosis in HIV-1/Mtb co-infected persons.

Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect.

The heart muscle diseases hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure in young, otherwise healthy, individuals. We conducted genome-wide association studies and multi-trait analyses in HCM (1,733 cases), DCM (5,521 cases) and nine left ventricular (LV) traits (19,260 UK Biobank participants with structurally normal hearts). We identified 16 loci associated with HCM, 13 with DCM and 23 with LV traits. We show strong genetic correlations between LV traits and cardiomyopathies, with opposing effects in HCM and DCM. Two-sample Mendelian randomization supports a causal association linking increased LV contractility with HCM risk. A polygenic risk score explains a significant portion of phenotypic variability in carriers of HCM-causing rare variants. Our findings thus provide evidence that polygenic risk score may account for variability in Mendelian diseases. More broadly, we provide insights into how genetic pathways may lead to distinct disorders through opposing genetic effects.

Defective ALC1 nucleosome remodeling confers PARPi sensitization and synthetic lethality with HRD.

Chromatin is a barrier to efficient DNA repair, as it hinders access and processing of certain DNA lesions. ALC1/CHD1L is a nucleosome-remodeling enzyme that responds to DNA damage, but its precise function in DNA repair remains unknown. Here we report that loss of ALC1 confers sensitivity to PARP inhibitors, methyl-methanesulfonate, and uracil misincorporation, which reflects the need to remodel nucleosomes following base excision by DNA glycosylases but prior to handover to APEX1. Using CRISPR screens, we establish that ALC1 loss is synthetic lethal with homologous recombination deficiency (HRD), which we attribute to chromosome instability caused by unrepaired DNA gaps at replication forks. In the absence of ALC1 or APEX1, incomplete processing of BER intermediates results in post-replicative DNA gaps and a critical dependence on HR for repair. Hence, targeting ALC1 alone or as a PARP inhibitor sensitizer could be employed to augment existing therapeutic strategies for HRD cancers.

Estimated 24-Hour Urinary Sodium Excretion and Incident Cardiovascular Disease and Mortality Among 398 628 Individuals in UK Biobank.

We report on an analysis to explore the association between estimated 24-hour urinary sodium excretion (surrogate for sodium intake) and incident cardiovascular disease (CVD) and mortality. Data were obtained from 398 628 UK Biobank prospective cohort study participants (40-69 years) recruited between 2006 and 2010, with no history of CVD, renal disease, diabetes mellitus or cancer, and cardiovascular events and mortality recorded during follow-up. Hazard ratios between 24-hour sodium excretion were estimated from spot urinary sodium concentrations across incident CVD and its components and all-cause and cause-specific mortality. In restricted cubic splines analyses, there was little evidence for an association between estimated 24-hour sodium excretion and CVD, coronary heart disease, or stroke; hazard ratios for CVD (95% CIs) for the 15th and 85th percentiles (2.5 and 4.2 g/day, respectively) compared with the 50th percentile of estimated sodium excretion (3.2 g/day) were 1.05 (1.01-1.10) and 0.96 (0.92-1.00), respectively. An inverse association was observed with heart failure, but that was no longer apparent in sensitivity analysis. A J-shaped association was observed between estimated sodium excretion and mortality. Our findings do not support a J-shaped association of estimated sodium excretion with CVD, although such an association was apparent for all-cause and cause-specific mortality across a wide range of diseases. Reasons for these differences are unclear; methodological limitations, including the use of estimating equations based on spot urinary data, need to be considered in interpreting our findings.

p-Value combiners for graphical modelling of EEG data in the frequency domain.

BACKGROUND: In the graphical modelling of brain data, we are interested in estimating connectivity between various regions of interest, and evaluating statistical significance in order to derive a network model. This process involves aggregating results across frequency ranges and several patients, in order to obtain an overall result that can serve to construct a graph. NEW METHOD: In this paper, we propose a method based on p-value combiners, which have never been used in applications to EEG data analysis. This new method is split into two aspects: frequency-wide tests and group-wide tests. The first step can be effectively adjusted to control for false detection rate. RESULTS: This two-step protocol is applied to EEG data collected from distinct groups of mental health patients, in order to draw graphical models for each group and highlight structural connectivity differences. Using the method proposed, we show that it is possible to reliably achieve this while effectively controlling for false connections detection. COMPARISON WITH EXISTING METHOD(S): Conventionally, the Holm's Stepdown procedure is used for this type of problem, as it is robust to type I errors. However, it is known to be conservative and prone to false negatives. Furthermore, unlike the proposed methods, it does not directly output a decision rule on whether to accept or reject a statement. CONCLUSIONS: The proposed methodology offers significant improvements over the stepdown procedure in terms of error rate and false negative rate across the network models, as well as in term of applicability.