Using multi-modal neuroimaging to characterise social brain specialisation in infants

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of functional specialisation in the infant brain is based on evidence from unitary imaging modalities and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG), metabolic rate, and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake infant. In 4- to 7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing, coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high-frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high-frequency brain activity. The development of simultaneous multimodal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain

ROS Promote Epigenetic Remodeling and Cardiac Dysfunction in Offspring Following Maternal Engineered Nanomaterial (ENM) Exposure

Background: Nano-titanium dioxide (nano-TiO2) is amongst the most widely utilized engineered nanomaterials (ENMs). However, little is known regarding the consequences maternal ENM inhalation exposure has on growing progeny during gestation. ENM inhalation exposure has been reported to decrease mitochondrial bioenergetics and cardiac function, though the mechanisms responsible are poorly understood. Reactive oxygen species (ROS) are increased as a result of ENM inhalation exposure, but it is unclear whether they impact fetal reprogramming. The purpose of this study was to determine whether maternal ENM inhalation exposure influences progeny cardiac development and epigenomic remodeling. Results: Pregnant FVB dams were exposed to nano-TiO2 aerosols with a mass concentration of 12.09 ± 0.26 mg/m3 starting at gestational day five (GD 5), for 6 h over 6 non-consecutive days. Aerosol size distribution measurements indicated an aerodynamic count median diameter (CMD) of 156 nm with a geometric standard deviation (GSD) of 1.70. Echocardiographic imaging was used to assess cardiac function in maternal, fetal (GD 15), and young adult (11 weeks) animals. Electron transport chain (ETC) complex activities, mitochondrial size, complexity, and respiration were evaluated, along with 5-methylcytosine, Dnmt1 protein expression, and Hif1α activity. Cardiac functional analyses revealed a 43% increase in left ventricular mass and 25% decrease in cardiac output (fetal), with an 18% decrease in fractional shortening (young adult). In fetal pups, hydrogen peroxide (H2O2) levels were significantly increased (~ 10 fold) with a subsequent decrease in expression of the antioxidant enzyme, phospholipid hydroperoxide glutathione peroxidase (GPx4). ETC complex activity IV was decreased by 68 and 46% in fetal and young adult cardiac mitochondria, respectively. DNA methylation was significantly increased in fetal pups following exposure, along with increased Hif1α activity and Dnmt1 protein expression. Mitochondrial ultrastructure, including increased size, was observed at both fetal and young adult stages following maternal exposure. Conclusions: Maternal inhalation exposure to nano-TiO2 results in adverse effects on cardiac function that are associated with increased H2O2 levels and dysregulation of the Hif1α/Dnmt1 regulatory axis in fetal offspring. Our findings suggest a distinct interplay between ROS and epigenetic remodeling that leads to sustained cardiac contractile dysfunction in growing and young adult offspring following maternal ENM inhalation exposure

Investigational chemotherapy and novel pharmacokinetic mechanisms for the treatment of breast cancer brain metastases

In women, breast cancer is the most common cancer diagnosis and second most common cause of cancer death. More than half of breast cancer patients will develop metastases to the bone, liver, lung, or brain. Breast cancer brain metastases (BCBM) confers a poor prognosis, as current therapeutic options of surgery, radiation, and chemotherapy rarely significantly extend life and are considered palliative. Within the realm of chemotherapy, the last decade has seen an explosion of novel chemotherapeutics involving targeting agents and unique dosage forms. We provide a historical overview of BCBM chemotherapy, review the mechanisms of new agents such as poly-ADP ribose polymerase inhibitors, cyclin-dependent kinase 4/6 inhibitors, phosphatidyl inositol 3-kinaseinhibitors, estrogen pathway antagonists for hormone-receptor positive BCBM; tyrosine kinase inhibitors, antibodies, and conjugates for HER2+ BCBM; repurposed cytotoxic chemotherapy for triple negative BCBM; and the utilization of these new agents and formulations in ongoing clinical trials. The mechanisms of novel dosage formulations such as nanoparticles, liposomes, pegylation, the concepts of enhanced permeation and retention, and drugs utilizing these concepts involved in clinical trials are also discussed. These new treatments provide a promising outlook in the treatment of BCBM

Crystal structure of the mitochondrial protein mitoNEET bound to a benze-sulfonide ligand

MitoNEET (gene cisd1) is a mitochondrial outer membrane [2Fe-2S] protein and is a potential drug target in several metabolic diseases. Previous studies have demonstrated that mitoNEET functions as a redox-active and pH-sensing protein that regulates mitochondrial metabolism, although the structural basis of the potential drug binding site(s) remains elusive. Here we report the crystal structure of the soluble domain of human mitoNEET with a sulfonamide ligand, furosemide. Exploration of the high-resolution crystal structure is used to design mitoNEET binding molecules in a pilot study of molecular probes for use in future development of mitochondrial targeted therapies for a wide variety of metabolic diseases, including obesity, diabetes and neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease

Crystal Structure of the Mitochondrial Protein mitoNEET Bound to a Benze-sulfonide Ligand

MitoNEET (gene cisd1) is a mitochondrial outer membrane [2Fe-2S] protein and is a potential drug target in several metabolic diseases. Previous studies have demonstrated that mitoNEET functions as a redox-active and pH-sensing protein that regulates mitochondrial metabolism, although the structural basis of the potential drug binding site(s) remains elusive. Here we report the crystal structure of the soluble domain of human mitoNEET with a sulfonamide ligand, furosemide. Exploration of the high-resolution crystal structure is used to design mitoNEET binding molecules in a pilot study of molecular probes for use in future development of mitochondrial targeted therapies for a wide variety of metabolic diseases, including obesity, diabetes and neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease

Using multi-modal neuroimaging to characterise social brain specialisation in infants

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of functional specialisation in the infant brain is based on evidence from unitary imaging modalities and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG), metabolic rate and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake infant. In 4-to-7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high frequency brain activity. The development of simultaneous multi-modal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain

Machine-learning to Stratify Diabetic Patients Using Novel Cardiac Biomarkers and Integrative Genomics

Background: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are two to four times more likely to develop cardiovascular diseases. While HbA1c remains the primary diagnostic for diabetics, its ability to predict long-term, health outcomes across diverse demographics, ethnic groups, and at a personalized level are limited. The purpose of this study was to provide a model for precision medicine through the implementation of machine-learning algorithms using multiple cardiac biomarkers as a means for predicting diabetes mellitus development. Methods: Right atrial appendages from 50 patients, 30 non-diabetic and 20 type 2 diabetic, were procured from the WVU Ruby Memorial Hospital. Machine-learning was applied to physiological, biochemical, and sequencing data for each patient. Supervised learning implementing SHapley Additive exPlanations (SHAP) allowed binary (no diabetes or type 2 diabetes) and multiple classifcation (no diabetes, prediabetes, and type 2 diabetes) of the patient cohort with and without the inclusion of HbA1c levels. Findings were validated through Logistic Regression (LR), Linear Discriminant Analysis (LDA), Gaussian Naïve Bayes (NB), Support Vector Machine (SVM), and Classifcation and Regression Tree (CART) models with tenfold cross validation. Results: Total nuclear methylation and hydroxymethylation were highly correlated to diabetic status, with nuclear methylation and mitochondrial electron transport chain (ETC) activities achieving superior testing accuracies in the predictive model (~84% testing, binary). Mitochondrial DNA SNPs found in the D-Loop region (SNP-73G, -16126C, and -16362C) were highly associated with diabetes mellitus. The CpG island of transcription factor A, mitochondrial (TFAM) revealed CpG24 (chr10:58385262, P=0.003) and CpG29 (chr10:58385324, P=0.001) as markers correlating with diabetic progression. When combining the most predictive factors from each set, total nuclear methylation and CpG24 methylation were the best diagnostic measures in both binary and multiple classifcation sets. Conclusions: Using machine-learning, we were able to identify novel as well as the most relevant biomarkers associated with type 2 diabetes mellitus by integrating physiological, biochemical, and sequencing datasets. Ultimately, this approach may be used as a guideline for future investigations into disease pathogenesis and novel biomarker discover

Fingerprinting coal-derived gases from the UK

The large-scale extraction of unconventional hydrocarbons in the United States has led to fears of methane contamination of shallow groundwaters. Differentiating between the deep gas released during extraction (shale gas, coal bed methane and underground coal gasification) and natural shallow-sourced methane is imperative for the monitoring and managing of environmental risks related to the extraction process. Here, for the first time, we present measurements of the major gas, and stable and noble gas isotope composition of coal bed methane (CBM) from central Scotland and coal mine methane (CMM) from central England, UK. The molecular (C1/(C2+C3) = 21 to 120) and stable isotope compositions (δ13CCH4 = -39.5 to -51.1‰; δDCH4 = -163 to -238‰) indicate a thermogenic origin for the methane. They are distinct from the majority of shallow-sourced gases in UK. Both sample suites exhibit high He concentrations (338 to 2980 ppmv) that are considerably above atmospheric and groundwater levels. Simple modelling shows that these high 4He concentrations cannot be solely derived from in situ production since coal deposition, and hence the majority is derived from the surrounding crust. The Scottish CBM contains a resolvable mantle He, Ne and Ar contribution that may originate from melts in the deep crust, demonstrating the UK coals have acted as a store for deep volatiles for 10s of millions of years. The high 4He in the coal-derived gases has the potential to be used as a novel diagnostic fingerprint to track fugitive release of deep methane from future unconventional gas extraction operations in the UK