Multimorbidity in bipolar disorder and under-treatment of cardiovascular disease: a cross sectional study

Background: Individuals with serious mental disorders experience poor physical health, especially increased rates of cardiometabolic morbidity and premature morbidity. Recent evidence suggests that individuals with schizophrenia have numerous comorbid physical conditions which may be under-recorded and under-treated but to date very few studies have explored this issue for bipolar disorder. Methods:We conducted a cross-sectional analysis of a dataset of 1,751,841 registered patients within 314 primary-care practices in Scotland, U.K. Bipolar disorder was identified using Read Codes recorded within electronic medical records. Data on 32 common chronic physical conditions were also assessed. Potential prescribing inequalities were evaluated by analyzing prescribing data for coronary heart disease (CHD) and hypertension. Results: Compared to controls, individuals with bipolar disorder were significantly less likely to have no recorded physical conditions (OR 0.59, 95% CI 0.54-0.63) and significantly more likely to have one physical condition (OR 1.27, 95% CI 1.16-1.39), two physical conditions (OR 1.45, 95% CI 1.30-1.62) and three or more physical conditions (OR 1.44, 95% CI 1.30-1.64). People with bipolar disorder also had higher rates of thyroid disorders, chronic kidney disease, chronic pain, chronic obstructive airways disease and diabetes but, surprisingly, lower recorded rates of hypertension and atrial fibrillation. People with bipolar disorder and comorbid CHD or hypertension were significantly more likely to be prescribed no antihypertensive or cholesterol-lowering medications compared to controls, and bipolar individuals with CHD or hypertension were significantly less likely to be on 2 or more antihypertensive agents. Conclusions: Individuals with bipolar disorder are similar to individuals with schizophrenia in having a wide range of comorbid and multiple physical health conditions. They are also less likely than controls to have a primary-care record of cardiovascular conditions such as hypertension and atrial fibrillation. Those with a recorded diagnosis of CHD or hypertension were less likely to be treated with cardiovascular medications and were treated less intensively. This study highlights the high physical healthcare needs of people with bipolar disorder, and provides evidence for a systematic under-recognition and under-treatment of cardiovascular disease in this group

Vaccination with DNA plasmids expressing Gn coupled to C3d or alphavirus replicons expressing Gn protects mice against rift valley fever virus

Background: Rift Valley fever (RVF) is an arthropod-borne viral zoonosis. Rift Valley fever virus (RVFV) is an important biological threat with the potential to spread to new susceptible areas. In addition, it is a potential biowarfare agent. Methodology/Principal Findings: We developed two potential vaccines, DNA plasmids and alphavirus replicons, expressing the Gn glycoprotein of RVFV alone or fused to three copies of complement protein, C3d. Each vaccine was administered to mice in an all DNA, all replicon, or a DNA prime/replicon boost strategy and both the humoral and cellular responses were assessed. DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn elicited high titer neutralizing antibodies that were similar to titers elicited by the live-attenuated MP12 virus. Mice vaccinated with an inactivated form of MP12 did elicit high titer antibodies, but these antibodies were unable to neutralize RVFV infection. However, only vaccine strategies incorporating alphavirus replicons elicited cellular responses to Gn. Both vaccines strategies completely prevented weight loss and morbidity and protected against lethal RVFV challenge. Passive transfer of antisera from vaccinated mice into naïve mice showed that both DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn elicited antibodies that protected mice as well as sera from mice immunized with MP12. Conclusion/Significance: These results show that both DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn administered alone or in a DNA prime/replicon boost strategy are effective RVFV vaccines. These vaccine strategies provide safer alternatives to using live-attenuated RVFV vaccines for human use. © 2010 Bhardwaj et al

Spatially-resolved electronic and vibronic properties of single diamondoid molecules

Diamondoids are a unique form of carbon nanostructure best described as hydrogen-terminated diamond molecules. Their diamond-cage structures and tetrahedral sp3 hybrid bonding create new possibilities for tuning electronic band gaps, optical properties, thermal transport, and mechanical strength at the nanoscale. The recently-discovered higher diamondoids (each containing more than three diamond cells) have thus generated much excitement in regards to their potential versatility as nanoscale devices. Despite this excitement, however, very little is known about the properties of isolated diamondoids on metal surfaces, a very relevant system for molecular electronics. Here we report the first molecular scale study of individual tetramantane diamondoids on Au(111) using scanning tunneling microscopy and spectroscopy. We find that both the diamondoid electronic structure and electron-vibrational coupling exhibit unique spatial distributions characterized by pronounced line nodes across the molecular surfaces. Ab-initio pseudopotential density functional calculations reveal that the observed dominant electronic and vibronic properties of diamondoids are determined by surface hydrogen terminations, a feature having important implications for designing diamondoid-based molecular devices.Comment: 16 pages, 4 figures. to appear in Nature Material

Generalization Error in Deep Learning

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

Oral chondroitin sulfate and prebiotics for the treatment of canine Inflammatory Bowel Disease: a randomized, controlled clinical trial

BACKGROUND Canine inflammatory bowel disease (IBD) is a chronic enteropathy of unknown etiology, although microbiome dysbiosis, genetic susceptibility, and dietary and/or environmental factors are hypothesized to be involved in its pathogenesis. Since some of the current therapies are associated with severe side effects, novel therapeutic modalities are needed. A new oral supplement for long-term management of canine IBD containing chondroitin sulfate (CS) and prebiotics (resistant starch, β-glucans and mannaoligosaccharides) was developed to target intestinal inflammation and oxidative stress, and restore normobiosis, without exhibiting any side effects. This double-blinded, randomized, placebo-controlled trial in dogs with IBD aims to evaluate the effects of 180 days administration of this supplement together with a hydrolyzed diet on clinical signs, intestinal histology, gut microbiota, and serum biomarkers of inflammation and oxidative stress. RESULTS Twenty-seven client-owned biopsy-confirmed IBD dogs were included in the study, switched to the same hydrolyzed diet and classified into one of two groups: supplement and placebo. Initially, there were no significant differences between groups (p > 0.05) for any of the studied parameters. Final data analysis (supplement: n = 9; placebo: n = 10) showed a significant decrease in canine IBD activity index (CIBDAI) score in both groups after treatment (p < 0.001). After treatment, a significant decrease (1.53-fold; p < 0.01) in histologic score was seen only in the supplement group. When groups were compared, the supplement group showed significantly higher serum cholesterol (p < 0.05) and paraoxonase-1 (PON1) levels after 60 days of treatment (p < 0.01), and the placebo group showed significantly reduced serum total antioxidant capacity (TAC) levels after 120 days (p < 0.05). No significant differences were found between groups at any time point for CIBDAI, WSAVA histologic score and fecal microbiota evaluated by PCR-restriction fragment length polymorphism (PCR-RFLP). No side effects were reported in any group. CONCLUSIONS The combined administration of the supplement with hydrolyzed diet over 180 days was safe and induced improvements in selected serum biomarkers, possibly suggesting a reduction in disease activity. This study was likely underpowered, therefore larger studies are warranted in order to demonstrate a supplemental effect to dietary treatment of this supplement on intestinal histology and CIBDAI

Impact of socioeconomic deprivation on rate and cause of death in severe mental illness

Background: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated.&lt;p&gt;&lt;/p&gt; Aims: To assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations.&lt;p&gt;&lt;/p&gt; Methods: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations.&lt;p&gt;&lt;/p&gt; Results: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = &#60;0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = &#60;0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = &#60;0.001 and 5.5%, p = &#60;0.001). Discussion and conclusions: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed

Climate impacts of energy technologies depend on emissions timing

Energy technologies emit greenhouse gases with differing radiative efficiencies and atmospheric lifetimes. Standard practice for evaluating technologies, which uses the global warming potential (GWP) to compare the integrated radiative forcing of emitted gases over a fixed time horizon, does not acknowledge the importance of a changing background climate relative to climate change mitigation targets. Here we demonstrate that the GWP misvalues the impact of CH[subscript 4]-emitting technologies as mid-century approaches, and we propose a new class of metrics to evaluate technologies based on their time of use. The instantaneous climate impact (ICI) compares gases in an expected radiative forcing stabilization year, and the cumulative climate impact (CCI) compares their time-integrated radiative forcing up to a stabilization year. Using these dynamic metrics, we quantify the climate impacts of technologies and show that high-CH[subscript 4]-emitting energy sources become less advantageous over time. The impact of natural gas for transportation, with CH[subscript 4] leakage, exceeds that of gasoline within 1–2 decades for a commonly cited 3 W m[superscript −2] stabilization target. The impact of algae biodiesel overtakes that of corn ethanol within 2–3 decades, where algae co-products are used to produce biogas and corn co-products are used for animal feed. The proposed metrics capture the changing importance of CH[subscript 4] emissions as a climate threshold is approached, thereby addressing a major shortcoming of the GWP for technology evaluation.New England University Transportation Center (DOT Grant DTRT07-G-0001

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine