Gilbert syndrome and the development of antiretroviral therapy-associated hyperbilirubinemia

BACKGROUND: Unconjugated hyperbilirubinemia results from Gilbert syndrome and from antiretroviral therapy (ART) containing protease inhibitors. An understanding of the interaction between genetic predisposition and ART may help to identify individuals at highest risk for developing jaundice. METHODS: We quantified the contribution of UGT1A1*28 and ART to hyperbilirubinemia by longitudinally modeling 1386 total bilirubin levels in 96 human immunodeficiency virus (HIV)-infected individuals during a median of 6 years. RESULTS: The estimated average bilirubin level was 8.8 micromol/L (0.51 mg/dL). Atazanavir increased bilirubin levels by 15 mu mol/L (0.87 mg/dL), and indinavir increased bilirubin levels by 8 micromol/L (0.46 mg/dL). Ritonavir, lopinavir, saquinavir, and nelfinavir had no or minimal effect on bilirubin levels. Homozygous UGT1A1*28 increased bilirubin levels by 5.2 micromol/L (0.3 mg/dL). As a consequence, 67% of individuals homozygous for UGT1A1*28 and receiving atazanavir or indinavir had > or =2 episodes of hyperbilirubinemia in the jaundice range (>43 micromol/L [>2.5 mg/dL]), versus 7% of those with the common allele and not receiving either of those protease inhibitors (P<.001). Efavirenz resulted in decreased bilirubin levels, which is consistent with the induction of UDP-glucuronosyltransferase 1A1. CONCLUSIONS: Genotyping for UGT1A1*28 before initiation of ART would identify HIV-infected individuals at risk for hyperbilirubinemia and decrease episodes of jaundice

Modeling the influence of APOC3, APOE, and TNF polymorphisms on the risk of antiretroviral therapy-associated lipid disorders.

BACKGROUND: Single-nucleotide polymorphisms in genes involved in lipoprotein and adipocyte metabolism may explain why dyslipidemia and lipoatrophy occur in some but not all antiretroviral therapy (ART)-treated individuals. METHODS: We evaluated the contribution of APOC3 -482C-->T, -455T-->C, and 3238C-->G; epsilon 2 and epsilon 4 alleles of APOE; and TNF -238G-->A to dyslipidemia and lipoatrophy by longitudinally modeling >2600 lipid determinations and 2328 lipoatrophy assessments in 329 ART-treated patients during a median follow-up period of 3.4 years. RESULTS: In human immunodeficiency virus (HIV)-infected individuals, the effects of variant alleles of APOE on plasma cholesterol and triglyceride levels and of APOC3 on plasma triglyceride levels were comparable to those reported in the general population. However, when treated with ritonavir, individuals with unfavorable genotypes of APOC3 and [corrected] APOE were at risk of extreme hypertriglyceridemia. They had median plasma triglyceride levels of 7.33 mmol/L, compared with 3.08 mmol/L in the absence of ART. The net effect of the APOE*APOC3*ritonavir interaction was an increase in plasma triglyceride levels of 2.23 mmol/L. No association between TNF -238G-->A and lipoatrophy was observed. CONCLUSIONS: Variant alleles of APOE and APOC3 contribute to an unfavorable lipid profile in patients with HIV. Interactions between genotypes and ART can lead to severe hyperlipidemia. Genetic analysis may identify patients at high risk for severe ritonavir-associated hypertriglyceridemia

Population pharmacokinetic modelling and evaluation of different dosage regimens for darunavir and ritonavir in HIV-infected individuals

Objectives Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. Methods The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM®). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. Results A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. Conclusions The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be propose

The HITRAN2016 molecular spectroscopic database

This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided

The HITRAN2020 Molecular Spectroscopic Database

The HITRAN database is a compilation of molecular spectroscopic parameters. It was established in the early 1970s and is used by various computer codes to predict and simulate the transmission and emission of light in gaseous media (with an emphasis on terrestrial and planetary atmospheres). The HITRAN compilation is composed of five major components: the line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, experimental infrared absorption cross-sections (for molecules where it is not yet feasible for representation in a line-by-line form), collision-induced absorption data, aerosol indices of refraction, and general tables (including partition sums) that apply globally to the data. This paper describes the contents of the 2020 quadrennial edition of HITRAN. The HITRAN2020 edition takes advantage of recent experimental and theoretical data that were meticulously validated, in particular, against laboratory and atmospheric spectra. The new edition replaces the previous HITRAN edition of 2016 (including its updates during the intervening years). All five components of HITRAN have undergone major updates. In particular, the extent of the updates in the HITRAN2020 edition range from updating a few lines of specific molecules to complete replacements of the lists, and also the introduction of additional isotopologues and new (to HITRAN) molecules: SO, CH3F, GeH4, CS2, CH3I and NF3. Many new vibrational bands were added, extending the spectral coverage and completeness of the line lists. Also, the accuracy of the parameters for major atmospheric absorbers has been increased substantially, often featuring sub-percent uncertainties. Broadening parameters associated with the ambient pressure of water vapor were introduced to HITRAN for the first time and are now available for several molecules. The HITRAN2020 edition continues to take advantage of the relational structure and efficient interface available at www.hitran.org and the HITRAN Application Programming Interface (HAPI). The functionality of both tools has been extended for the new edition

The 2015 edition of the GEISA spectroscopic database

The GEISA database (Gestion et Etude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information) has been developed and maintained by the ARA/ABC(t) group at LMD since 1974. GEISA is constantly evolving, taking into account the best available spectroscopic data. This paper presents the 2015 release of GEISA (GEISA-2015), which updates the last edition of 2011 and celebrates the 40th anniversary of the database. Significant updates and additions have been implemented in the three following independent databases of GEISA. The “line parameters database” contains 52 molecular species (118 isotopologues) and transitions in the spectral range from 10−6 to 35,877.031 cm−1, representing 5,067,351 entries, against 3,794,297 in GEISA-2011. Among the previously existing molecules, 20 molecular species have been updated. A new molecule (SO3) has been added. HDO, isotopologue of H2O, is now identified as an independent molecular species. Seven new isotopologues have been added to the GEISA-2015 database. The “cross section sub-database” has been enriched by the addition of 43 new molecular species in its infrared part, 4 molecules (ethane, propane, acetone, acetonitrile) are also updated; they represent 3% of the update. A new section is added, in the near-infrared spectral region, involving 7 molecular species: CH3CN, CH3I, CH3O2, H2CO, HO2, HONO, NH3. The “microphysical and optical properties of atmospheric aerosols sub-database” has been updated for the first time since 2003. It contains more than 40 species originating from NCAR and 20 from the ARIA archive of Oxford University. As for the previous versions, this new release of GEISA and associated management software facilities are implemented and freely accessible on the AERIS/ESPRI atmospheric chemistry data center website

Ecological and genetic analysis of copper and streptomycin resistance in Pseudomonas syringae pv. syringae

Strains of Pseudomonas syringae pv. syringae resistant to copper, streptomycin, or both compounds were recovered from symptomless and diseased tissue of four woody hosts in three nurseries in Oklahoma. In strains resistant to copper and streptomycin (Cu^r Sm^r), resistance to both compounds was cotransferred with a single plasmid which was either 68, 190, or 220 kilobase pairs (kb). All Cu^s Sm^r strains contained a 68-kb conjugative plasmid. Cu^r Sm^s, strains contained one plasmid which varied in size from 60 to 73 kb. All conjugative plasmids which transferred streptomycin resistance contained sequences homologous to the strA and strB Sm^r genes from the broad-host-range plasmid RSF1010. The Sm^r determinant was subsequently cloned from a 68-kb Cu^r Sm^r plasmid designated pPSR1. A restriction map detailing the organization of the homologous Sm^r genes from pPSR1 and RSF1010 and cloned Sm^r genes from P. syringae pv. papulans and Xanthomonas campestris pv. vesicatoria revealed the conservation of all sites studied. The Cu^r genes cloned from P. syringae pv. tomato PT23 and X. campestris pv. vesicatoria XV10 did not hybridize to the Cu^r plasmids identified in the present study, indicating that copper resistance in these P. syringae pv. syringae strains may be conferred by a distinct genetic determinant.Peer reviewedPlant Patholog

The HITRAN2020 molecular spectroscopic database

The HITRAN database is a compilation of molecular spectroscopic parameters. It was established in the early 1970s and is used by various computer codes to predict and simulate the transmission and emission of light in gaseous media (with an emphasis on terrestrial and planetary atmospheres). The HITRAN compilation is composed of five major components: the line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, experimental infrared absorption cross-sections (for molecules where it is not yet feasible for representation in a line-by-line form), collision-induced absorption data, aerosol indices of refraction, and general tables (including partition sums) that apply globally to the data. This paper describes the contents of the 2020 quadrennial edition of HITRAN. The HITRAN2020 edition takes advantage of recent experimental and theoretical data that were meticulously validated, in particular, against laboratory and atmospheric spectra. The new edition replaces the previous HITRAN edition of 2016 (including its updates during the intervening years). All five components of HITRAN have undergone major updates. In particular, the extent of the updates in the HITRAN2020 edition range from updating a few lines of specific molecules to complete replacements of the lists, and also the introduction of additional isotopologues and new (to HITRAN) molecules: SO, CH3F, GeH4, CS2, CH3I and NF3. Many new vibrational bands were added, extending the spectral coverage and completeness of the line lists. Also, the accuracy of the parameters for major atmospheric absorbers has been increased substantially, often featuring sub-percent uncertainties. Broadening parameters associated with the ambient pressure of water vapor were introduced to HITRAN for the first time and are now available for several molecules. The HITRAN2020 edition continues to take advantage of the relational structure and efficient interface available at www.hitran.org and the HITRAN Application Programming Interface (HAPI). The functionality of both tools has been extended for the new edition

Global assessment of marine plastic exposure risk for oceanic birds

Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species