UBA1 Depletion Sensitizes Ovarian, Breast, and Colorectal Cell Lines to Olaparib PARP inhibitor

https://openworks.mdanderson.org/sumexp22/1097/thumbnail.jp

RLIP76, a non-ABC transporter, and drug resistance in epilepsy

BACKGROUND: Permeability of the blood-brain barrier is one of the factors determining the bioavailability of therapeutic drugs and resistance to chemically different antiepileptic drugs is a consequence of decreased intracerebral accumulation. The ABC transporters, particularly P-glycoprotein, are known to play a role in antiepileptic drug extrusion, but are not by themselves sufficient to fully explain the phenomenon of drug-resistant epilepsy. Proteomic analyses of membrane protein differentially expressed in epileptic foci brain tissue revealed the frequently increased expression of RLIP76/RALBP1, a recently described non-ABC multi-specific transporter. Because of a significant overlap in substrates between P-glycoprotein and RLIP76, present studies were carried out to determine the potential role of RLIP76 in AED transport in the brain. RESULTS: RLIP76 was expressed in brain tissue, preferentially in the lumenal surface of endothelial cell membranes. The expression was most prominent in blood brain barrier tissue from excised epileptic foci. Saturable, energy-dependent, anti-gradient transport of both phenytoin and carbamazepine were demonstrated using recombinant RLIP76 reconstituted into artificial membrane liposomes. Immunotitration studies of transport activity in crude membrane vesicles prepared from whole-brain tissue endothelium showed that RLIP76 represented the dominant transport mechanism for both drugs. RLIP76(-/- )knockout mice exhibited dramatic toxicity upon phenytoin administration due to decreased drug extrusion mechanisms at the blood-brain barrier. CONCLUSION: We conclude that RLIP76 is the predominant transporter of AED in the blood brain barrier, and that it may be a transporter involved in mechanisms of drug-resistant epilepsy

Recent Approaches of Intranasal to Brain Drug Delivery System

While the intranasal administration of drugs to the brain has been gaining both research attention and regulatory success over the past several years, key fundamental and translational challenges remain to fully leveraging the promise of this drug delivery pathway for improving the treatment of various neurological and psychiatric illnesses. In response, this review highlights the current state of understanding of the nose-to-brain drug delivery pathway and how both biological and clinical barriers to drug transport using the pathway can been addressed, as illustrated by demonstrations of how currently approved intranasal sprays leverage these pathways to enable the design of successful therapies. Moving forward, aiming to better exploit the understanding of this fundamental pathway, we also outline the development of nanoparticle systems that show improvement in delivering approved drugs to the brain and how engineered nanoparticle formulations could aid in breakthroughs in terms of delivering emerging drugs and therapeutics while avoiding systemic adverse effects

Platelet aggregation, mean platelet volume and plasma fibrinogen as risk factors for acute myocardial infarction

Background: The Aim of this study was to assess the role of platelet aggregation, mean platelet volume (MPV) and plasma fibrinogen levels in the pathogenesis of acute myocardial infarction (AMI).Methods: A prospective case control study was conducted on 30 cases of AMI and 30 normal healthy age and sex matched controls. The cases and controls were investigated for platelet aggregation studies (done in platelet rich plasma (PRP) using light transmission chrono-log optical aggregometer), MPV (measured by automated cell counter) and plasma fibrinogen levels (estimated by Clauss method).Results: The mean platelet aggregation (%) in cases AMI was 57.61±11.91 which was significantly higher compared with 35.00±10.40 for healthy controls (p<0.001). Using Receiver Operating Characteristic (ROC) analysis, most patients of AMI had a platelet aggregability of ≥49% on optical aggregometry (sensitivity = 83.3 % and specificity = 93.7%). The MPV (fL) in cases of AMI was 8.04±0.39 which was significantly larger when compared with 7.67±0.43 for controls (p= 0.001). The mean plasma fibrinogen concentration in cases of AMI was 383.1±48.3mg/dl which was significantly higher when compared with 271.33±57.7mg/dl for healthy controls (p<0.001).Conclusions: Platelet hyperaggregability, elevated MPV and plasma fibrinogen levels are found in patients with AMI and contribute significantly to risk of developing coronary thrombosis. These variables should be considered as additional screening tools to identify individuals at increased risk of developing AMI

RLIP76, a Glutathione-Conjugate Transporter, Plays a Major Role in the Pathogenesis of Metabolic Syndrome

PURPOSE: Characteristic hypoglycemia, hypotriglyceridemia, hypocholesterolemia, lower body mass, and fat as well as pronounced insulin-sensitivity of RLIP76⁻/⁻ mice suggested to us the possibility that elevation of RLIP76 in response to stress could itself elicit metabolic syndrome (MSy). Indeed, if it were required for MSy, drugs used to treat MSy should have no effect on RLIP76⁻/⁻ mice. RESEARCH DESIGN AND METHODS: Blood glucose (BG) and lipid measurements were performed in RLIP76⁺/⁺ and RLIP76⁻/⁻ mice, using Ascensia Elite Glucometer® for glucose and ID Labs kits for cholesterol and triglycerides assays. The ultimate effectors of gluconeogenesis are the three enzymes: PEPCK, F-1,6-BPase, and G6Pase, and their expression is regulated by PPARγ and AMPK. The activity of these enzymes was tested by protocols standardized by us. Expressions of RLIP76, PPARα, PPARγ, HMGCR, pJNK, pAkt, and AMPK were performed by Western-blot and tissue staining. RESULTS: The concomitant activation of AMPK and PPARγ by inhibiting transport activity of RLIP76, despite inhibited activity of key glucocorticoid-regulated hepatic gluconeogenic enzymes like PEPCK, G6Pase and F-1,6-BP in RLIP76⁻/⁻ mice, is a salient finding of our studies. The decrease in RLIP76 protein expression by rosiglitazone and metformin is associated with an up-regulation of PPARγ and AMPK. CONCLUSIONS/SIGNIFICANCE: All four drugs, rosiglitazone, metformin, gemfibrozil and atorvastatin failed to affect glucose and lipid metabolism in RLIP76⁻/⁻ mice. Studies confirmed a model in which RLIP76 plays a central role in the pathogenesis of MSy and RLIP76 loss causes profound and global alterations of MSy signaling functions. RLIP76 is a novel target for single-molecule therapeutics for metabolic syndrome

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator