Biomedical subjects

Caroline Reid

Publications and source records attributed to Caroline Reid.

7 recordsLinked to original sources

PubMed2006

From motivation to behaviour: a model of reward sensitivity, overeating, and food preferences in the risk profile for obesity.

The reinforcing effects of addictive drugs and palatable foods are regulated, at least in part, by a common biological mechanism. The reactivity or sensitivity of these brain reward regions have been found to correlate significantly with the risk for a variety of drug addictions. Sensitivity to Reward (STR) is conceptualised as a psycho-biological personality trait rooted firmly in the availability of dopamine in the mesocorticolimbic ('common reward') pathways, and as such is a good candidate for studying motivational factors and eating behaviours. The purpose of the present study was to examine whether STR was related to behaviours that contribute to excess body weight. Structural equation modelling procedures were used with a sample of healthy adult women (n=151). We hypothesised that STR would positively predict overeating and a preference for foods high in fat and sugar; and that these two behaviour would, in turn, predict a higher Body Mass Index. Results provided an excellent fit of the model to our data confirming our view that a personality trait like STR can only influence a physical condition like body weight indirectly by the way it co-varies with behaviours that contribute directly to variation in the outcome variable.

Adult↗

PubMed2006

Discordances between interpretation algorithms for genotypic resistance to protease and reverse transcriptase inhibitors of human immunodeficiency virus are subtype dependent.

The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V + 63P + 36I/V for subtype C and 82I + 63P + 36I + 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A + 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R + 115 M and 118I + 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtype-dependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype.

Algorithms↗

PubMed2003

Comparative evaluation of three computerized algorithms for prediction of antiretroviral susceptibility from HIV type 1 genotype.

OBJECTIVES: To compare three methods for using HIV-1 genotype to predict antiretroviral drug susceptibility. METHODS: We applied three genotypic interpretation algorithms to 478 reverse transcriptase (RT) and 410 protease sequences for which phenotypic data were available. Sequences were obtained from clinical practice and from published sequences in the Stanford HIV-1 RT and Protease Sequence Database. The genotypic interpretation algorithms included: Stanford HIVdb program (HIVdb), the Visible Genetics/Bayer Diagnostics Guidelines 6.0 (VGI) and a genotypic interpretation program (AntiRetroScan, ARS) developed at the University of Siena, Italy. Genotypic interpretations were normalized to a three-level output: susceptible, intermediate and resistant. Discordances were defined as differences between genotype and phenotype for the same virus isolate. Discordances for which an isolate was considered susceptible by one test but resistant by another test were considered major discordances. RESULTS: The frequency of major discordances between genotype and phenotype was 10.6, 13.7 and 15.7% for ARS, VGI and HIVdb, respectively (P < 0.0001 for ARS versus HIVdb and for ARS versus VGI; P = 0.002 for VGI versus HIVdb). The correlation between genotype and phenotype was highest for non-nucleoside RT inhibitors and lowest for nucleoside RT inhibitors. Half of the major discordances involved stavudine, didanosine and zalcitabine. The concordance among the three genotypic algorithms was high, with weighted Kappa values ranging between 0.76 and 0.84 for the pairwise comparisons between each of the algorithms. CONCLUSIONS: Genotype interpretation algorithms correctly predict phenotype in 85-90% of cases, but the rate of concordance is not uniformly distributed among different drugs. These data provide insight into the potential additional benefit derived from phenotyping.

Algorithms↗

PubMed2003

HIV-1 protease and reverse transcriptase mutation patterns responsible for discordances between genotypic drug resistance interpretation algorithms.

Several rules-based algorithms have been developed to interpret results of HIV-1 genotypic resistance tests. To assess the concordance of these algorithms and to identify sequences causing interalgorithm discordances, we applied four publicly available algorithms to the sequences of isolates from 2,045 individuals in northern California. Drug resistance interpretations were classified as S for susceptible, I for intermediate, and R for resistant. Of 30,675 interpretations (2,045 sequences x 15 drugs), 4.4% were completely discordant, with at least one algorithm assigning an S and another an R; 29.2% were partially discordant, with at least one algorithm assigning an S and another an I, or at least one algorithm assigning an I and another an R; and 66.4% displayed complete concordance, with all four algorithms assigning the same interpretation. Discordances between nucleoside reverse transcriptase inhibitor interpretations usually resulted from several simple, frequently occurring mutational patterns. Discordances between protease inhibitor interpretations resulted from a larger number of more complex mutation patterns. Discordances between nonnucleoside reverse transcriptase inhibitor interpretations were uncommon and resulted from a small number of individual drug resistance mutations. Determining the clinical significance of these mutation patterns responsible for interalgorithm discordances will improve interalgorithm concordance and the accuracy of genotypic resistance interpretation.

Algorithms↗

PubMed2003

Accuracy of the TRUGENE HIV-1 genotyping kit.

Drug resistance and poor virological responses are associated with well-characterized mutations in the viral reading frames that encode the proteins that are targeted by currently available antiretroviral drugs. An integrated system was developed that includes target gene amplification, DNA sequencing chemistry (TRUGENE HIV-1 Genotyping Kit), and hardware and interpretative software (the OpenGene DNA Sequencing System) for detection of mutations in the human immunodeficiency virus type 1 (HIV-1) protease and reverse transcriptase sequences. The integrated system incorporates reverse transcription-PCR from extracted HIV-1 RNA, a coupled amplification and sequencing step (CLIP), polyacrylamide gel electrophoresis, semiautomated analysis of data, and generation of an interpretative report. To assess the accuracy and robustness of the assay system, 270 coded plasma specimens derived from nine patients were sent to six laboratories for blinded analysis. All specimens contained HIV-1 subtype B viruses. Results of 270 independent assays were compared to "gold standard" consensus sequences of the virus populations determined by sequence analysis of 16 to 20 clones of viral DNA amplicons derived from two independent PCRs using primers not used in the kit. The accuracy of the integrated system for nucleotide base identification was 98.7%, and the accuracy for codon identification at 54 sites associated with drug resistance was 97.6%. In a separate analysis of plasma spiked with infectious molecular clones, the assay reproducibly detected all 72 different drug resistance mutations that were evaluated. There were no significant differences in accuracy between laboratories, between technologists, between kit lots, or between days. This integrated assay system for the detection of HIV-1 drug resistance mutations has a high degree of accuracy and reproducibility in several laboratories.

Anti-HIV Agents↗

PubMed2003

Performance characteristics of the TRUGENE HIV-1 Genotyping Kit and the Opengene DNA Sequencing System.

The TRUGENE HIV-1 Genotyping Kit and OpenGene DNA Sequencing System are designed to sequence the protease (PR)- and reverse transcriptase (RT)-coding regions of human immunodeficiency virus type 1 (HIV-1) pol. Studies were undertaken to determine the accuracy of this assay system in detecting resistance-associated mutations and to determine the effects of RNA extraction methods, anticoagulants, specimen handling, and potentially interfering substances. Samples were plasma obtained from HIV-infected subjects or seronegative plasma to which viruses derived from wild-type and mutant infectious molecular clones (IMC) of HIV-1 were added. Extraction methods tested included standard and UltraSensitive AMPLICOR HIV-1 MONITOR, QIAGEN viral RNA extraction mini kit, and QIAGEN Ultra HIV extraction kit, and NASBA manual HIV-1 quantitative NucliSens. Sequence data from test sites were compared to a "gold standard" reference sequence to determine the percent agreement. Comparisons between test and reference sequences at the nucleotide level showed 97.5 to 100% agreement. Similar results were obtained regardless of extraction method, regardless of use of EDTA or acid citrate dextrose as anticoagulant, and despite the presence of triglycerides, bilirubin, hemoglobin, antiretroviral drugs, HIV-2, hepatitis C virus (HCV), HBV, cytomegalovirus, human T-cell leukemia virus type 1 (HTLV-1), or HTLV-2. Samples with HIV-1 RNA titers of >or=1,000 copies/ml gave consistent results. The TRUGENE HIV-1 Genotyping Kit and OpenGene DNA Sequencing System consistently generate highly accurate sequence data when tested with IMC-derived HIV and patient samples.

Anticoagulants↗

PubMed2002

Total syntheses of the marine pyrrole alkaloids polycitone A and B.

Polycitone B (2) was obtained in four steps from pyrrole dicarboxylic acid 3, including Friedel-Crafts reaction of the corresponding acid chloride with anisole. The conversion of 2 into polycitone A (1) was achieved in two steps via Mitsunobu alkylation of the pyrrolic NH group. The synthesis of polycitone A proceeds in 18% overall yield and offers the possibility of varying the substituents on the pyrrole ring.

Alkaloids↗