Quasi-diffusion magnetic resonance imaging (QDI): A fast, high b-value diffusion imaging technique.

To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1-4 min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps. QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s-1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value. We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena

A zebrafish model for Mycobacterium leprae granulomatous infection

Understanding the pathogenesis of leprosy granulomas has been hindered by a paucity of tractable experimental animal models. Mycobacterium leprae, which causes leprosy, grows optimally at ~30°C, so we sought to model granulomatous disease in the ectothermic zebrafish. We find noncaseating granulomas develop rapidly, and eventually eradicate infection. rag1 mutant zebrafish, which lack lymphocytes, also form noncaseating granulomas with similar kinetics, but these control infection more slowly. Our findings establish the zebrafish as a facile, genetically tractable model for leprosy, and reveal the interplay between innate and adaptive immune determinants mediating leprosy granuloma formation and function

A Macrophage Response to Mycobacterium leprae Phenolic Glycolipid Initiates Nerve Damage in Leprosy

$\textit{Mycobacterium leprae}$ causes leprosy and is unique among mycobacterial diseases in producing peripheral neuropathy. This debilitating morbidity is attributed to axon demyelination resulting from direct interaction of the $\textit{M. leprae}$-specific phenolic glycolipid 1 (PGL-1) with myelinating glia and their subsequent infection. Here, we use transparent zebrafish larvae to visualize the earliest events of $\textit{M. leprae}$-induced nerve damage. We find that demyelination and axonal damage are not directly initiated by $\textit{M. leprae}$ but by infected macrophages that patrol axons; demyelination occurs in areas of intimate contact. PGL-1 confers this neurotoxic response on macrophages: macrophages infected with $\textit{M. marinum}$-expressing PGL-1 also damage axons. PGL-1 induces nitric oxide synthase in infected macrophages, and the resultant increase in reactive nitrogen species damages axons by injuring their mitochondria and inducing demyelination. Our findings implicate the response of innate macrophages to $\textit{M. leprae}$ PGL-1 in initiating nerve damage in leprosy.This work was supported by an A.P. Giannini Foundation Postdoctoral Fellowship, an NIH training grant (T32 AI1007411), and an NIH NRSA Postdoctoral Fellowship (AI104240) to C.A.M.; an NSF Predoctoral Fellowship and NIH training grant T32 AI55396 to C.J.C.; a UCLA Clinical Translational Science Institute grant (UL1TR001881 to K.K.S.); K08AR066545 to P.O.S.; U19AI111224 and R01AI049313 to D.B.M.; an NIH grant (R01AR064582) to A.S.; the NIH Director’s Pioneer Award, an NIH MERIT award (R37AI054503), and a Wellcome Trust Principal Research Fellowship to L.R

High resolution human leukocyte antigen (HLA) class I and class II allele typing in Mexican mestizo women with sporadic breast cancer: case-control study

<p>Abstract</p> <p>Background</p> <p>The development of breast cancer is multifactorial. Hormonal, environmental factors and genetic predisposition, among others, could interact in the presentation of breast carcinoma. Human leukocyte antigen (HLA) alleles play an important role in immunity (cellular immunity) and may be important genetic traits. HLAAllele-specific interaction has not been well established. Recently, several studies had been conducted in order to do so, but the results are controversial and in some instances contradictory.</p> <p>Methods</p> <p>We designed a case-control study to quantify the association of HLA class I and II genes and breast cancer. HLA typing was performed by high resolution sequence-specific oligotyping after DNA amplification (PCR-SSOP) of 100 breast cancer Mexican mestizo patients and 99 matched healthy controls.</p> <p>Results</p> <p>HLA-A frequencies that we were able to observe that there was no difference between both groups from the statistical viewpoint. HLA-B*1501 was found three times more common in the case group (OR, 3.714; <it>p </it>= 0.031). HLA-Cw is not a marker neither for risk, nor protection for the disease, because we did not find significant statistical differences between the two groups. DRB1*1301, which is expressed in seven cases and in only one control, observing an risk increase of up to seven times and DRB1*1602, which behaves similarly in being present solely in the cases (OR, 16.701; 95% CI, 0.947 – 294.670). DQ*0301-allele expression, which is much more common in the control group and could be protective for the presentation of the disease (OR, 0.078; 95% CI, 0.027–0.223, <it>p </it>= 0.00001).</p> <p>Conclusion</p> <p>Our results reveal the role of the MHC genes in the pathophysiology of breast cancer, suggesting that in the development of breast cancer exists a disorder of immune regulation. The triggering factor seems to be restricted to certain ethnic groups and certain geographical regions since the relevant MHC alleles are highly diverse. This is the first study in Mexican population where high resolutions HLA typing has been performed in order to try to establish an association with malignancy.</p

A Bayesian Approach to Analyse Genetic Variation within RNA Viral Populations

The development of modern and affordable sequencing technologies has allowed the study of viral populations to an unprecedented depth. This is of particular interest for the study of within-host RNA viral populations, where variation due to error-prone polymerases can lead to immune escape, antiviral resistance and adaptation to new host species. Methods to sequence RNA virus genomes include reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a molecular biology technique widely used to amplify DNA from an RNA template. The method itself relies on the in vitro synthesis of copy DNA from RNA followed by multiple cycles of DNA amplification. However, this method introduces artefactual errors that can act as confounding factors when the sequence data are analysed. Although there are a growing number of published studies exploring the intra- and inter-host evolutionary dynamics of RNA viruses, the complexity of the methods used to generate sequences makes it difficult to produce probabilistic statements about the likely sources of observed sequence variants. This complexity is further compounded as both the depth of sequencing and the length of the genome segment of interest increase. Here we develop a Bayesian method to characterise and differentiate between likely structures for the background viral population. This approach can then be used to identify nucleotide sites that show evidence of change in the within-host viral population structure, either over time or relative to a reference sequence (e.g. an inoculum or another source of infection), or both, without having to build complex evolutionary models. Identification of these sites can help to inform the design of more focussed experiments using molecular biology tools, such as site-directed mutagenesis, to assess the function of specific amino acids. We illustrate the method by applying to datasets from experimental transmission of equine influenza, and a pre-clinical vaccine trial for HIV-1

Risk prediction models with incomplete data with application to prediction of estrogen receptor-positive breast cancer: prospective data from the Nurses' Health Study

Introduction A number of breast cancer risk prediction models have been developed to provide insight into a woman\u27s individual breast cancer risk. Although circulating levels of estradiol in postmenopausal women predict subsequent breast cancer risk, whether the addition of estradiol levels adds significantly to a model\u27s predictive power has not previously been evaluated. Methods Using linear regression, the authors developed an imputed estradiol score using measured estradiol levels (the outcome) and both case status and risk factor data (for example, body mass index) from a nested case-control study conducted within a large prospective cohort study and used multiple imputation methods to develop an overall risk model including both risk factor data from the main cohort and estradiol levels from the nested case-control study. Results The authors evaluated the addition of imputed estradiol level to the previously published Rosner and Colditz log-incidence model for breast cancer risk prediction within the larger Nurses\u27 Health Study cohort. The follow-up was from 1980 to 2000; during this time, 1,559 invasive estrogen receptor-positive breast cancer cases were confirmed. The addition of imputed estradiol levels significantly improved risk prediction; the age-specific concordance statistic increased from 0.635 ± 0.007 to 0.645 ± 0.007 (P \u3c 0.001) after the addition of imputed estradiol. Conclusion Circulating estradiol levels in postmenopausal women appear to add to other lifestyle factors in predicting a woman\u27s individual risk of breast cancer

Co-expression of CD147 (EMMPRIN), CD44v3-10, MDR1 and monocarboxylate transporters is associated with prostate cancer drug resistance and progression

Background: The aim of this study is to seek an association between markers of metastatic potential, drug resistance-related protein and monocarboxylate transporters in prostate cancer (CaP). Methods: We evaluated the expression of invasive markers (CD147, CD44v3-10), drug-resistance protein (MDR1) and monocarboxylate transporters (MCT1 and MCT4) in CaP metastatic cell lines and CaP tissue microarrays (n=140) by immunostaining. The co-expression of CD147 and CD44v3-10 with that of MDR1, MCT1 and MCT4 in CaP cell lines was evaluated using confocal microscopy. The relationship between the expression of CD147 and CD44v3-10 and the sensitivity (IC50) to docetaxel in CaP cell lines was assessed using MTT assay. The relationship between expression of CD44v3-10, MDR1 and MCT4 and various clinicopathological CaP progression parameters was examined. Results: CD147 and CD44v3-10 were co-expressed with MDR1, MCT1 and MCT4 in primary and metastatic CaP cells. Both CD147 and CD44v3-10 expression levels were inversely related to docetaxel sensitivity (IC50) in metastatic CaP cell lines. Overexpression of CD44v3-10, MDR1 and MCT4 was found in most primary CaP tissues, and was significantly associated with CaP progression. Conclusions: Our results suggest that the overexpression of CD147, CD44v3-10, MDR1 and MCT4 is associated with CaP progression. Expression of both CD147 and CD44v3-10 is correlated with drug resistance during CaP metastasis and could be a useful potential therapeutic target in advanced disease

Demographic and occupational predictors of early response to a mailed invitation to enroll in a longitudinal health study

BACKGROUND: Often in survey research, subsets of the population invited to complete the survey do not respond in a timely manner and valuable resources are expended in recontact efforts. Various methods of improving response have been offered, such as reducing questionnaire length, offering incentives, and utilizing reminders; however, these methods can be costly. Utilizing characteristics of early responders (refusal or consent) in enrollment and recontact efforts may be a unique and cost-effective approach for improving the quality of epidemiologic research. METHODS: To better understand early responders of any kind, we compared the characteristics of individuals who explicitly refused, consented, or did not respond within 2 months from the start of enrollment into a large cohort study of US military personnel. A multivariate polychotomous logistic regression model was used to estimate the effect of each covariate on the odds of early refusal and on the odds of early consent versus late/non-response, while simultaneously adjusting for all other variables in the model. RESULTS: From regression analyses, we found many similarities between early refusers and early consenters. Factors associated with both early refusal and early consent included older age, higher education, White race/ethnicity, Reserve/Guard affiliation, and certain information technology and support occupations. CONCLUSION: These data suggest that early refusers may differ from late/non-responders, and that certain characteristics are associated with both early refusal and early consent to participate. Structured recruitment efforts that utilize these differences may achieve early response, thereby reducing mail costs and the use of valuable resources in subsequent contact efforts

The Florey Adelaide Male Ageing Study (FAMAS): Design, procedures & participants

<p>Abstract</p> <p>Background</p> <p>The Florey Adelaide Male Ageing Study (FAMAS) examines the reproductive, physical and psychological health, and health service utilisation of the ageing male in Australia. We describe the rationale for the study, the methods used participant response rates, representativeness and attrition to date.</p> <p>Methods</p> <p>FAMAS is a longitudinal study involving approximately 1200 randomly selected men, aged 35–80 years and living in the north – west regions of Adelaide. Respondents were excluded at screening if they were considered incapable of participating because of immobility, language, or an inability to undertake the study procedures. Following a telephone call to randomly selected households, eligible participants were invited to attend a baseline clinic measuring a variety of biomedical and socio-demographic factors. Beginning in 2002, these clinics are scheduled to reoccur every five years. Follow-up questionnaires are completed annually. Participants are also invited to participate in sub-studies with selected collaborators.</p> <p>Results</p> <p>Of those eligible to participate, 45.1% ultimately attended a clinic. Non-responders were more likely to live alone, be current smokers, have a higheevalence of self-reported diabetes and stroke, and lower levels of hypercholesterolemia. Comparisons with the Census 2001 data showed that participants matched the population for most key demographics, although younger groups and never married men were under-represented and elderly participants were over-represented. To date, there has been an annual loss to follow-up of just over 1%.</p> <p>Conclusion</p> <p>FAMAS allows a detailed investigation into the effects of bio-psychosocial and behavioural factors on the health and ageing of a largely representative group of Australian men.</p