Light my elbows: a cycling jacket incorporating electronic yarn

There is a need for illuminated cycle clothing that is comfortable and safe when cycling, and stylish to wear during other activities. It is particularly challenging to integrate lighting within textiles without compromising the drape and comfort of the textile structure. A team of electronics, textiles and fashion specialists was formed to design and make an illuminated jacket for use by cyclists. The jacket incorporates bespoke woven panels that integrate electronic yarns within the pattern. These were designed and made for this project, with fluorescent and retroreflective yarns also included in the weave. LEDs integrated within the electronic yarns illuminate the elbows of the jacket, without causing constraint or adding excess volume. The movement of the jacket elbows during cycling widens the body outline and makes the lighting eye-catching. The collaboration between electronics and textiles experts overcame challenges including development of electrical circuitry designed specifically to fit into the jacket unobtrusively, without interfering with movement or rucksack straps. Electrical connections were required between the electronic yarns assimilated within the weave. Standard, rigid solder joints would have been difficult to form without damaging the cloth and would have been liable to breakage within the garment structure, so embroidery techniques were used to create flexible, conductive connections. The illuminated jacket provides a working prototype, demonstrating the potential for further collaborative ventures in which electronics are integrated into garments that are stylish, functional and ‘wearable’. Further interdisciplinary research will include the development of additional wearable prototypes that enhance safety and wellbeing, whilst addressing the recycling of the textiles and garments, including the safe separation and disposal of electronic yarn and other components that provide electrical functionality

Population variation in ovarian function

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30638/1/0000280.pd

Ears of the Armadillo: Global Health Research and Neglected Diseases in Texas

Neglected tropical diseases (NTDs) have\ud been recently identified as significant public\ud health problems in Texas and elsewhere in\ud the American South. A one-day forum on the\ud landscape of research and development and\ud the hidden burden of NTDs in Texas\ud explored the next steps to coordinate advocacy,\ud public health, and research into a\ud cogent health policy framework for the\ud American NTDs. It also highlighted how\ud U.S.-funded global health research can serve\ud to combat these health disparities in the\ud United States, in addition to benefiting\ud communities abroad

Improving the evidence base of Markov models used to estimate the costs of scaling up antiretroviral programmes in resource-limited settings

<p>Abstract</p> <p>Background</p> <p>Despite concerns about affordability and sustainability, many models of the lifetime costs of antiretroviral therapy (ART) used in resource limited settings are based on data from small research cohorts, together with pragmatic assumptions about life-expectancy. This paper revisits these modelling assumptions in order to provide input to future attempts to model the lifetime costs and the costs of scaling up ART.</p> <p>Methods</p> <p>We analysed the determinants of costs and outcomes in patients receiving ART in line with standard World Health Organization (WHO) guidelines for resource poor settings in a private sector managed ART programme in South Africa. The cohort included over 5,000 patients with up to 4 years (median 19 months) on ART. Generalized linear and Cox proportional hazards regression models were used to establish cost and outcome determinants respectively.</p> <p>Results</p> <p>The key variables associated with changes in mean monthly costs were: being on the second line regimen; receiving ART from 4 months prior to 4 months post treatment initiation; having a recent or current CD4 count <50 cells/µL or 50-199 cells/µl; having mean ART adherence <75% as determined by monthly pharmacy refill data; and having a current or recent viral load >100,000 copies/mL. In terms of the likelihood of dying, the key variables were: baseline CD4 count<50 cells/µl (particularly during the first 4 months on treatment); current CD4 count <50 cells/µl and 50-199 cells/µl (particularly during later periods on treatment); and being on the second line regimen. Being poorly adherent and having an unsuppressed viral load was also associated with a higher likelihood of dying.</p> <p>Conclusions</p> <p>While there are many unknowns associated with modelling the resources needed to scale-up ART, our analysis has suggested a number of key variables which can be used to improve the state of the art of modelling ART. While the magnitude of the effects associated with these variables would be likely to differ in other settings, the variables influencing costs and survival are likely to be generalizable. This is of direct relevance to those concerned about assessing the long-term costs and sustainability of expanded access to ART.</p

Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome

<p>Abstract</p> <p>Background</p> <p>Biomarker-based assessments of biological samples are widespread in clinical, pre-clinical, and epidemiological investigations. We previously developed serum metabolomic profiles assessed by HPLC-separations coupled with coulometric array detection that can accurately identify <it>ad libitum </it>fed and caloric-restricted rats. These profiles are being adapted for human epidemiology studies, given the importance of energy balance in human disease.</p> <p>Methods</p> <p>Human plasma samples were biochemically analyzed using HPLC separations coupled with coulometric electrode array detection.</p> <p>Results</p> <p>We identified these markers/metabolites in human plasma, and then used them to determine which human samples represent blinded duplicates with 100% accuracy (N = 30 of 30). At least 47 of 61 metabolites tested were sufficiently stable for use even after 48 hours of exposure to shipping conditions. Stability of some metabolites differed between individuals (N = 10 at 0, 24, and 48 hours), suggesting the influence of some biological factors on parameters normally considered as analytical.</p> <p>Conclusion</p> <p>Overall analytical precision (mean median CV, ~9%) and total between-person variation (median CV, ~50–70%) appear well suited to enable use of metabolomics markers in human clinical trials and epidemiological studies, including studies of the effect of caloric intake and balance on long-term cancer risk.</p

Impact of Pre-adapted HIV Transmission

Human Leukocyte Antigen class I (HLA) restricted CD8+ T lymphocyte (CTL) responses are critical to HIV-1 control. Although HIV can evade these responses, the longer-term impact of viral escape mutants remains unclear, since these variants can also reduce intrinsic viral fitness. To address this question, we here develop a metric to determine the degree of HIV adaptation to an HLA profile. We demonstrate that transmission of viruses pre-adapted to the HLA molecules expressed in the recipient is associated with impaired immunogenicity, elevated viral load and accelerated CD4 decline. Furthermore, the extent of pre-adaptation among circulating viruses explains much of the variation in outcomes attributed to expression of certain HLA alleles. Thus, viral pre-adaptation exploits “holes” in the immune response. Accounting for these holes may be critical for vaccine strategies seeking to elicit functional responses from viral variants, and to HIV cure strategies requiring broad CTL responses to achieve successful eradication of HIV reservoirs

Geographic and temporal trends in the molecular epidemiology and genetic mechanisms of transmitted HIV-1 drug resistance:an individual-patient- and sequence-level meta-analysis

Regional and subtype-specific mutational patterns of HIV-1 transmitted drug resistance (TDR) are essential for informing first-line antiretroviral (ARV) therapy guidelines and designing diagnostic assays for use in regions where standard genotypic resistance testing is not affordable. We sought to understand the molecular epidemiology of TDR and to identify the HIV-1 drug-resistance mutations responsible for TDR in different regions and virus subtypes.status: publishe

Latent growth curve modelling of positive and negative symptom trajectories in first-episode psychosis from baseline to long-term follow-up

© 2017 Dr. Susan Margaret HarriganBackground: Comparatively little is known about the way in which the positive and negative symptoms of psychosis change in the first year following the initial psychotic episode. The importance of these short-term trajectories (STT) as a predictor of long-term symptomatic outcomes has not been widely explored. Furthermore, the role of short-term change as a mediator of effects of patient presenting features, such as gender, age at onset of psychosis, duration of untreated psychosis, premorbid functioning, and of DSM-IV psychotic diagnosis, on long-term symptom levels, is unclear. Any mediating role of short term changes are of interest because they may help explain the mechanism by which presenting factors affect long-term symptoms. This thesis modelled trajectories of positive and negative symptoms following an initial psychotic episode in 413 first-episode patients to better understand the mechanisms underlying course of recovery. Methods: Latent growth curve (LGC) methodologies were used to model the data. These methods offer a contemporary approach for the analysis of longitudinal data. LGC models address the pitfalls associated with the longitudinal designs that conventional methods cannot, including attrition, missing data and variability in follow-up assessment intervals between individuals, and additionally, are able to deal with zero-inflated models and non-normal data. LGC methods also offer other advantages, including explicitly modelling change both within and between individuals, and allows for potential predictors of variability in symptom trajectories to be identified. Results: Change in positive symptoms conformed optimally to a non-linear trajectory, whilst changes in affective flattening, alogia, avolition, and anhedonia, were linear. Individuals varied significantly in their values at the beginning of the trajectory on the four negative symptom subscales, and on positive symptoms, and in their rates of change over the short-term trajectory on alogia, avolition and anhedonia. Short-term symptom change was partly accounted for by clinical presenting features. The most notable finding was the pivotal role played by the STTs in predicting long-term symptoms levels, independently of the effects of DUP, premorbid functioning, gender, age at onset of psychosis, admission symptom levels, and baseline DSM-IV diagnosis. The association between the STTs and long-term negative symptoms, in particular, was notable. Higher initial trajectory levels, and increasing change over the 1-year interval subsequent to initial recovery, predicted worse long-term symptomatic outcomes. The STTs also mediated the effects of participant presenting features on long-term symptomatic positive and negative symptom outcome. Conclusion: These findings imply that symptom changes in the period after admission to the service is critical to how a young person’s symptoms continue to evolve in the longer term. It suggests that the STT may be a sentinel for long-term negative symptoms. The importance of the STT is underlined, particularly when considered alongside its role as a causal pathway for the effects of DUP, premorbid functioning, age at onset of psychosis, and baseline DSM-IV diagnosis, on long-term symptomatic outcome. Greater focus on the treatment of negative symptoms in psychotic disorders is long overdue, in contrast to the range of relatively established treatments for positive symptoms. New, smaller studies, with frequent assessments, are required to investigate the development, course, and interaction amongst negative symptoms. This is necessary to develop an appreciation of the underlying processes that might inform new treatment strategies