Diet patterns are associated with demographic factors and nutritional status in south Indian children

The burden of non-communicable chronic disease (NCD) in India is increasing. Diet and body composition 'track' from childhood into adult life and contribute to the development of risk factors for NCD. Little is known about the diet patterns of Indian children. We aimed to identify diet patterns and study associations with body composition and socio-demographic factors in the Mysore Parthenon Study cohort. We collected anthropometric and demographic data from children aged 9.5 years (n = 538). We also administered a food frequency questionnaire and measured fasting blood concentrations of folate and vitamin B12. Using principal component analysis, we identified two diet patterns. The 'snack and fruit' pattern was characterised by frequent intakes of snacks, fruit, sweetened drinks, rice and meat dishes and leavened breads. The 'lacto-vegetarian' pattern was characterised by frequent intakes of finger millet, vegetarian rice dishes, yoghurt, vegetable dishes and infrequent meat consumption. Adherence to the 'snack and fruit' pattern was associated with season, being Muslim and urban dwelling. Adherence to the lacto-vegetarian pattern was associated with being Hindu, rural dwelling and a lower maternal body mass index. The 'snack and fruit' pattern was negatively associated with the child's adiposity. The lacto-vegetarian pattern was positively associated with blood folate concentration and negatively with vitamin B12 concentration. This study provides new information on correlates of diet patterns in Indian children and how diet relates to nutritional status. Follow-up of these children will be important to determine the role of these differences in diet in the development of risk factors for NCD including body composition

A patient-derived explant (PDE) model of hormone-dependent cancer

Breast and prostate cancer research to date has largely been predicated on the use of cell lines in vitro or in vivo. These limitations have led to the development of more clinically relevant models, such as organoids or murine xenografts that utilize patient-derived material; however, issues related to low take rate, long duration of establishment, and the associated costs constrain use of these models. This study demonstrates that ex vivo culture of freshly resected breast and prostate tumor specimens obtained from surgery, termed patient-derived explants (PDEs), provides a high-throughput and cost-effective model that retains the native tissue architecture, microenvironment, cell viability, and key oncogenic drivers. The PDE model provides a unique approach for direct evaluation of drug responses on an individual patient's tumor, which is amenable to analysis using contemporary genomic technologies. The ability to rapidly evaluate drug efficacy in patient-derived material has high potential to facilitate implementation of personalized medicine approaches.Margaret M. Centenera, Theresa E. Hickey, Shalini Jindal, Natalie K. Ryan, Preethi Ravindranathan, Hisham Mohammed, Jessica L. Robinson, Matthew J. Schiewer, Shihong Ma, Payal Kapur, Peter D. Sutherland, Clive E. Hoffmann, Claus G. Roehrborn, Leonard G. Gomella, Jason S. Carroll, Stephen N. Birrell, Karen E. Knudsen, Ganesh V. Raj, Lisa M. Butler, Wayne D. Tille

Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017

Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri

Rational targeting of the Androgen receptor interactome in prostate cancer

AbstractPreethi Ravindranathan, Wayne Tilley and Ganesh V. Ra

A Multi-Sensor System for Silkworm Cocoon Gender Classification via Image Processing and Support Vector Machine

Sericulture is traditionally a labor-intensive rural-based industry. In modern contexts, the development of process automation faces new challenges related to quality and efficiency. During the silkworm farming life cycle, a common issue is represented by the gender classification of the cocoons. Improper cocoon separation negatively affects quantity and quality of the yield resulting in disruptive bottlenecks for the productivity. To tackle this issue, this paper proposes a multi sensor system for silkworm cocoons gender classification and separation. Utilizing a load sensor and a digital camera, the system acquires weight and digital images from individual silkworm cocoons. An image processing procedure is then applied to extract significant shape-related features from each image instance, which, combined with the weight data, are provided as inputs to train a Support Vector Machine-based pattern classifier for gender classification. Subsequently, an air blower mechanism and a conveyor system sort the cocoons into their respective bins. The developed system was trained and tested on two different types of silkworm cocoons breeds, respectively CSR2 and Pure Mysore. The system performances are finally discussed in terms of accuracy, robustness and computation time

Tailoring peptidomimetics for targeting protein-protein interactions

Abstract not availableOmar N. Akram, David J. DeGraff, Jonathan H. Sheehan, Wayne D. Tilley, Robert J. Matusik, Jung-Mo Ahn, and Ganesh V. Ra