Cytochrome P450 1B1 and 12/15 Lipoxygenase Interaction in Paraventricular Nucleus in Angiotensin II-induced Hypertension in Females

Background: Angiotensin (Ang) II releases arachidonic acid (AA) from tissue phospholipids that is metabolized by 12/15-lipoxygenase (ALOX15) generating 12(S)- and 15(S)-hydroxyeicosatetraenoic acid (HETE) which have been implicated in cardiovascular and renal diseases. This study was conducted to investigate a) the contribution of ALOX15 to Ang II-induced hypertension and associated pathogenesis in female mice, and b) the interaction between the cytochrome P450 (CYP)1B1-generated metabolite of 17β-estradiol (E2) (2-methoxyestradiol, 2-ME) and ALOX15 in the paraventricular nucleus (PVN) as a mechanism that protects against Ang II-induced hypertension and its associated pathogenesis in female mice. Methods: Experiments were conducted in intact and ovariectomized (OVX) wild type (WT), alox15 knockout (ALOX15KO) and CYP1B1KO female mice. Ang II (700 ng/kg/min) was infused subcutaneously by osmotic pumps for 2 weeks evaluation of hypertension and associated pathogenesis. Blood pressure (BP) was measured by tail-cuff and confirmed by radiotelemetry. Adenoviral probes including adenovirus (Ad)-green fluorescence (GFP)-ALOX15-short hairpin (sh)RNA, Ad-GFP-ALOX15-DNA, and their respective controls Ad-scrambled shRNA and Ad-GFP-DNA, 12(S)-HETE and 2-ME were injected in the brain using stereotaxic technique, either selectively in PVN or intracerebroventricularly via ICV cannula implanted in the right lateral ventricle to study their roles on Ang II-induced hypertension. Histological, immunohistochemical, and fluorescence microscopy and biochemical techniques were employed to determine the pathophysiological changes in tissues. ELISA was used for the analysis of sex steroids and eicosanoids. Results: Our results demonstrate that the effects of Ang II to increase BP, impair autonomic function and increase renal reactive oxygen species (ROS) production and plasma 12(S)-HETE but not 15(S)-HETE level without altering renal function in intact WT mice were exacerbated in OVX-WT mice. Ang II also increased renal alox15 mRNA, urine 12(S)-HETE, water intake, urine output, decreased osmolality, increased urinary excretion of vasopressin prosegment copeptin, protein/creatinine ratio, and caused renal hypertrophy, fibrosis, and inflammation in OVX-WT mice. These effects of Ang II were attenuated in ALOX15KO mice. Moreover, the Ang II-induced hypertension that was also exaggerated in intact CYP1B1KO mice compared to WT mice was minimized by selective alox15 gene knockdown in PVN by transduction with Ad-ALOX15-shRNA and the restoration of Ang II-induced hypertension by selective reconstitution of alox15 gene in PVN by transduction with Ad-ALOX15-DNA in intact ALOX15KO mice was further exacerbated in OVX-ALOX15KO mice. Furthermore, ICV-12(S)-HETE that restored Ang II-induced increase in BP, impairment of autonomic function, neuroinflammation and renal pathogenesis in intact ALOX15KO mice, further exacerbated these effects of Ang II in OVX-ALOX15KO mice. Finally, ICV-2-ME that reduced the alox15 mRNA expression and 12(S)-HETE content in PVN minimized the hypertensive effects of Ang II, including BP, autonomic impairment, neuroinflammation and renal pathogenesis in OVX-ALOX15KO with the restoration of alox15 gene in PVN by transduction ICV with Ad-ALOX15-DNA. Conclusion: These data suggest that 17β-estradiol plays a critical role in female mice in protecting against Ang II-induced hypertension and associated pathogenesis, most likely via inhibition of ALOX15 activation and reduced production of 12(S)-HETE in the PVN. Therefore, the selective inhibitors of ALOX15 or 12(S)-HETE receptor antagonists could be useful for treating hypertension and its pathogenesis in postmenopausal, hypoestrogenic women or females with ovarian failure. These data also elucidate how drugs that inhibit CYP1B1 activity can be beneficial for treating hypertension and its pathogenesis in males but can be detrimental in females. The effect of alox15 gene polymorphism in pre-and postmenopausal females to determine its impact on the contribution of AA-ALOX15 derived 12(S)-HETE in hypertension and its pathogenesis is also warranted

Carbon Nanotube Gas Sensor Using Neural Networks

The need to identify the presence and quantify the concentrations of gases and vapors is ubiquitous in NASA missions and societal applications. Sensors for air quality monitoring in crew cabins and ISS have been actively under development (Ref. 1). In particular, measuring the concentration of CO2 and NH3 is important because high concentrations of these gases pose a risk to ISS crew health. Detection of fuel and oxidant leaks in crew vehicles is critical for ensuring mission safety. Accurate gas and vapor concentrations can be measured, but this typically requires bulky and expensive instrumentation. Recently, inexpensive sensors with low power demands have been fabricated for use on the International Space Station (ISS). Carbon Nanotube (CNT) based chemical sensors are one type of these sensors. CNT sensors meet the requirements for low cost and ease of fabrication for deployment on the ISS. However, converting the measured signal from the sensors to human readable indicators of atmospheric air quality and safety is challenging. This is because it is difficult to develop an analytical model that maps the CNT sensor output signal to gas concentration. Training a neural network on CNT sensor data to predict gas concentration is more effective than developing an analytic approach to calculate the concentration from the same data set. With this in mind a neural network was created to tackle this challenge of converting the measured signal into CO2 and NH3 concentration values

Detrimental orofacial manifestations of dengue and dengue hemorrhagic fever clinical case series, review of the causes, complications, and vaccine strategies

It is estimated that there are about 10% of cases that involve oral mucosa in patients with dengue hemorrhagic fever (HF), and even less number of cases in dengue fever (DF) has been reported. This leads to a lack of future investigation. Aims and objectivesThis review intends to enhance the understanding of the epidemiology, clinical features involving the oral manifestations, and treatment of dengue disease. Design and Methods Several search engines, including PubMed, World Health Organization (WHO), and Pan American Health Organization (PAHO) websites were utilized for the literature search using the terms dengue and dengue shock syndrome.Results Dengue is a major arthropod-borne viral disease of humans. Its presentation is protean and varies from an undifferentiated viral syndrome to viral HF and severe shock. The early diagnosis of the oral manifestations, hemorrhagic, or mucocutaneous, may lead to timely clinical evaluation of the patient with signs and symptoms suggestive of dengue viral infection.Conclusion The specific therapy for dengue infections is still undiscovered. Proper care, including vector control and prevention of mosquito bites, may be beneficial. However, the role of dental professionals and general practitioners is important in identifying the oral manifestations of dengue viral infection and providing specific diagnosis and effective treatment to the patients

Interactive Multi-Instrument Database of Solar Flares

The fundamental motivation of the project is that the scientific output of solar research can be greatly enhanced by better exploitation of the existing solar/heliosphere space-data products jointly with ground-based observations. Our primary focus is on developing a specific innovative methodology based on recent advances in "big data" intelligent databases applied to the growing amount of high-spatial and multi-wavelength resolution, high-cadence data from NASA's missions and supporting ground-based observatories. Our flare database is not simply a manually searchable time-based catalog of events or list of web links pointing to data. It is a preprocessed metadata repository enabling fast search and automatic identification of all recorded flares sharing a specifiable set of characteristics, features, and parameters. The result is a new and unique database of solar flares and data search and classification tools for the Heliophysics community, enabling multi-instrument/multi-wavelength investigations of flare physics and supporting further development of flare-prediction methodologies

Stock Liquidity and Firm Value: The Mediating Role of Capital Structure

Despite the substantial volume of research on the direct relationship between stock liquidity and firm value, no agreement has been reached on this nexus. This relationship may be influenced by some other intervening factors which have not been captured in the empirical studies. The present study aims to explore the link between stock liquidity and firm value and empirically tests the mediating role of capital structure on this relationship in the Indian context. Using sample data from 97 National Stock Exchange (NSE) listed top non-financial firms from 2010 to 2019 and adopting the Baron and Kenny approach, the results show that higher stock liquidity leads to a greater firm value. Furthermore, firms with liquid stocks are found to have significantly lower leverage. The results also confirm that capital structure fully mediates the relationship between stock liquidity and firm value. The empirical findings have important managerial implications when it comes to devising policies to maximise firms’ value

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns

Heliophysics Portal - Multi-Instrument Database of Solar Flares

No abstract availabl

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Architecture and capabilities of a data warehouse for ATM research

This paper describes the design, implementation, and use of a data warehouse that supports air traffic management (ATM) research at NASA’s Ames Research Center. The data warehouse, dubbed Sherlock, has been in development since 2009 and is a crucial piece of the ATM research infrastructure used by Ames and its partners. Sherlock comprises several components, including a database, a webbased user interface, and supplementary services for query and visualization. The information stored includes raw data collected from the National Airspace System (NAS), parsed and processed data, derived data, and reports derived from pre-defined queries. The raw data include a variety of flight information from live streams of FAA operational systems, weather observations and forecasts, and NAS advisories and statistics. The modified data comprise parsed and merged data sources and metadata, enabling parameterized searches for data of interest. The derived data represent the results of research analyses deemed to be of significant interest to a wide cross-section of users. Sherlock is implemented on an Oracle 11g database, with supplemental services built on open-source packages and custom software. It contains over 20 TB of data spanning several years, and more data are added daily. It has supported several research studies, such as finding similar days in the NAS and predicting imposition of traffic flow management restrictions. Planned enhancements include integrated search across data sources and the capability for large-scale analytics