Beyond literacy and numeracy in patient provider communication: Focus groups suggest roles for empowerment, provider attitude and language

<p>Abstract</p> <p>Background</p> <p>Although the number of people living in the United States with limited English proficiency (LEP) is substantial, the impact of language on patients' experience of provider-patient communication has been little explored.</p> <p>Methods</p> <p>We conducted a series of 12 exploratory focus groups in English, Spanish and Cantonese to elicit discussion about patient-provider communication, particularly with respect to the concerns of the health literacy framework, i.e. ability to accurately understand, interpret and apply information given by providers. Within each language, 2 groups had high education and 2 had low education participants to partially account for literacy levels, which cannot be assessed consistently across three languages. Eighty-five (85) adults enrolled in the focus groups. The resulting video tapes were transcribed, translated and analyzed via content analysis.</p> <p>Results</p> <p>We identified 5 themes: 1) language discordant communication; 2) language concordant communication; 3) empowerment; 4) providers' attitudes; 5) issues with the health care system. Despite efforts by facilitators to elicit responses related to cognitive understanding, issues of interpersonal process were more salient, and respondents did not readily separate issues of accurate understanding from their overall narratives of experience with health care and illness. Thematic codes often appeared to be associated with education level, language and/or culture.</p> <p>Conclusion</p> <p>Our most salient finding was that for most of our participants there was no clear demarcation between literacy and numeracy, language interpretation, health communication, interpersonal relations with their provider and the rest of their experience with the health care system.</p

Objective sequence-based subfamily classifications of mouse homeodomains reflect their in vitro DNA-binding preferences

Classifying proteins into subgroups with similar molecular function on the basis of sequence is an important step in deriving reliable functional annotations computationally. So far, however, available classification procedures have been evaluated against protein subgroups that are defined by experts using mainly qualitative descriptions of molecular function. Recently, in vitro DNA-binding preferences to all possible 8-nt DNA sequences have been measured for 178 mouse homeodomains using protein-binding microarrays, offering the unprecedented opportunity of evaluating the classification methods against quantitative measures of molecular function. To this end, we automatically derive homeodomain subtypes from the DNA-binding data and independently group the same domains using sequence information alone. We test five sequence-based methods, which use different sequence-similarity measures and algorithms to group sequences. Results show that methods that optimize the classification robustness reflect well the detailed functional specificity revealed by the experimental data. In some of these classifications, 73–83% of the subfamilies exactly correspond to, or are completely contained in, the function-based subtypes. Our findings demonstrate that certain sequence-based classifications are capable of yielding very specific molecular function annotations. The availability of quantitative descriptions of molecular function, such as DNA-binding data, will be a key factor in exploiting this potential in the future.Canadian Institutes of Health Research (MOP#82940)Sickkids FoundationOntario Research FundNational Science Foundation (U.S.)National Human Genome Research Institute (U.S.) (R01 HG003985

Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion

Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intra-axonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with square-wave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 60-80 mT/m) was found to be between 4 and 8 μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300 mT/m, the limit was reduced to between 2 and 5 μm

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p

Genomic Islands as a Marker to Differentiate between Clinical and Environmental Burkholderia pseudomallei

Burkholderia pseudomallei, as a saprophytic bacterium that can cause a severe sepsis disease named melioidosis, has preserved several extra genes in its genome for survival. The sequenced genome of the organism showed high diversity contributed mainly from genomic islands (GIs). Comparative genome hybridization (CGH) of 3 clinical and 2 environmental isolates, using whole genome microarrays based on B. pseudomallei K96243 genes, revealed a difference in the presence of genomic islands between clinical and environmental isolates. The largest GI, GI8, of B. pseudomallei was observed as a 2 sub-GI named GIs8.1 and 8.2 with distinguishable %GC content and unequal presence in the genome. GIs8.1, 8.2 and 15 were found to be more common in clinical isolates. A new GI, GI16c, was detected on chromosome 2. Presences of GIs8.1, 8.2, 15 and 16c were evaluated in 70 environmental and 64 clinical isolates using PCR assays. A combination of GIs8.1 and 16c (positivity of either GI) was detected in 70% of clinical isolates and 11.4% of environmental isolates (P<0.001). Using BALB/c mice model, no significant difference of time to mortality was observed between K96243 isolate and three isolates without GIs under evaluation (P>0.05). Some virulence genes located in the absent GIs and the difference of GIs seems to contribute less to bacterial virulence. The PCR detection of 2 GIs could be used as a cost effective and rapid tool to detect potentially virulent isolates that were contaminated in soil

Cross-talk between circadian clocks, sleep-wake cycles, and metabolic networks: Dispelling the darkness.

Integration of knowledge concerning circadian rhythms, metabolic networks, and sleep-wake cycles is imperative for unraveling the mysteries of biological cycles and their underlying mechanisms. During the last decade, enormous progress in circadian biology research has provided a plethora of new insights into the molecular architecture of circadian clocks. However, the recent identification of autonomous redox oscillations in cells has expanded our view of the clockwork beyond conventional transcription/translation feedback loop models, which have been dominant since the first circadian period mutants were identified in fruit fly. Consequently, non-transcriptional timekeeping mechanisms have been proposed, and the antioxidant peroxiredoxin proteins have been identified as conserved markers for 24-hour rhythms. Here, we review recent advances in our understanding of interdependencies amongst circadian rhythms, sleep homeostasis, redox cycles, and other cellular metabolic networks. We speculate that systems-level investigations implementing integrated multi-omics approaches could provide novel mechanistic insights into the connectivity between daily cycles and metabolic systems.ABR is a Wellcome Trust Senior Clinical Fellow and receives funding from the Wellcome Trust (Grant No. 100333/Z/12/Z), the European Research Council (ERC Starting Grant No. 281348, MetaCLOCK), the European Molecular Biology Organization (EMBO) Young Investigators Programme, and the Lister Institute of Preventative Medicine. SR is supported by the Wellcome Trust.This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/bies.20150005

Development of a World Health Organization International Reference Panel for different genotypes of hepatitis E virus for nucleic acid amplification testing.

Globally, hepatitis E virus (HEV) is a major cause of acute viral hepatitis. Epidemiology and clinical presentation of hepatitis E vary greatly by location and are affected by the HEV genotype. Nucleic acid amplification technique (NAT)-based assays are important for the detection of acute HEV infection as well for monitoring chronic cases of hepatitis E. The aim of the study was to evaluate a panel of samples containing different genotypes of HEV for use in nucleic NAT-based assays. The panel of samples comprises eleven different members including HEV genotype 1a (2 strains), 1e, 2a, 3b, 3c, 3e, 3f, 4c, 4g as well as a human isolate related to rabbit HEV. Each laboratory assayed the panel members directly against the 1 World Health Organization (WHO) International Standard (IS) for HEV RNA (6329/10) which is based upon a genotype 3 a strain. The samples for evaluation were distributed to 24 laboratories from 14 different countries and assayed on three separate days. Of these, 23 participating laboratories returned a total of 32 sets of data; 17 from quantitative assays and 15 from qualitative assays. The assays used consisted of a mixture of in-house developed and commercially available assays. The results showed that all samples were detected consistently by the majority of participants, although in some cases, some samples were detected less efficiently. Based on the results of the collaborative study the panel (code number 8578/13) was established as the "1st International Reference Panel (IRP) for all HEV genotypes for NAT-based assays" by the WHO Expert Committee on Biological Standardization. This IRP will be important for assay validation and ensuring adequate detection of different genotypes and clinically important sub-genotypes of HEV

Evolution and Taxonomic Classification of Human Papillomavirus 16 (HPV16)-Related Variant Genomes: HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67

Human papillomavirus 16 (HPV16) species group (alpha-9) of the Alphapapillomavirus genus contains HPV16, HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67. These HPVs account for 75% of invasive cervical cancers worldwide. Viral variants of these HPVs differ in evolutionary history and pathogenicity. Moreover, a comprehensive nomenclature system for HPV variants is lacking, limiting comparisons between studies.DNA from cervical samples previously characterized for HPV type were obtained from multiple geographic regions to screen for novel variants. The complete 8 kb genomes of 120 variants representing the major and minor lineages of the HPV16-related alpha-9 HPV types were sequenced to capture maximum viral heterogeneity. Viral evolution was characterized by constructing phylogenic trees based on complete genomes using multiple algorithms. Maximal and viral region specific divergence was calculated by global and pairwise alignments. Variant lineages were classified and named using an alphanumeric system; the prototype genome was assigned to the A lineage for all types.The range of genome-genome sequence heterogeneity varied from 0.6% for HPV35 to 2.2% for HPV52 and included 1.4% for HPV31, 1.1% for HPV33, 1.7% for HPV58 and 1.1% for HPV67. Nucleotide differences of approximately 1.0% - 10.0% and 0.5%-1.0% of the complete genomes were used to define variant lineages and sublineages, respectively. Each gene/region differs in sequence diversity, from most variable to least variable: noncoding region 1 (NCR1) /noncoding region 2 (NCR2) >upstream regulatory region (URR)> E6/E7 > E2/L2 > E1/L1.These data define maximum viral genomic heterogeneity of HPV16-related alpha-9 HPV variants. The proposed nomenclature system facilitates the comparison of variants across epidemiological studies. Sequence diversity and phylogenies of this clinically important group of HPVs provides the basis for further studies of discrete viral evolution, epidemiology, pathogenesis and preventative/therapeutic interventions