PeRsOnalised nutriTion for hEalthy livINg: The PROTEIN project

Personalised nutrition is a novel public health strategy aiming to promote positive diet and lifestyle changes. Tailored dietary and physical activity advice may be more appropriate than a generalised ‘one‐size‐fits‐all’ approach as it is more biologically relevant to the individual. Information and computing technology, smartphones and mobile applications have become an integral part of modern life and thereby present the opportunity for novel methods to encourage individuals to lead a healthier lifestyle. This article introduces the European Union‐funded PROTEIN project (PeRsOnalised nutriTion for hEalthy livINg) consortium and introduces the associated work packages. The primary objective of the PROTEIN project is to produce a novel adaptable mobile application suite based on sound nutrition and physical activity advice from experts in their field, accessible to all population groups, with differing health outcomes, whose behaviour can be tracked with a variety of sensors and health hazard perception. The mobile application ‘ecosystem’ that will be developed by the consortium includes a platform, mobile suite, cloud services, artificial intelligence advisor, game suite, modelling of expert’s knowledge, users’ behaviour data collection, data analysis and a dashboard for healthcare professionals. It is proposed that users will find the provision of personalised nutrition advice and real‐time data capture through a smartphone application useful, and importantly, will be encouraged by this to make positive health behaviour changes.     

Men with unilateral Achilles tendinopathy have impaired balance on the symptomatic side

Objectives

To investigate single leg standing balance in males with mid-portion Achilles tendinopathy (AT).

Infant Health and Development Program for low birth weight, premature infants: program elements, family participation, and child intelligence.

The Infant Health and Development Program was an eight-site randomized controlled trial testing the efficacy of early intervention to enhance the cognitive, behavioral, and health status of low birth weight, premature infants. The 377 intervention families received for the first 3 years of life: (1) pediatric follow-up, (2) home visits, (3) parent support groups, and (4) a systematic educational program provided in specialized child development centers. The control group (n = 608) received the same pediatric follow-up and referral services only. This paper describes the delivery of the intervention and its outcomes. A Family Participation Index that was the sum of participation frequencies in each of the program modalities unique to the intervention revealed that program implementation was not different across the eight sites. Index scores did not vary systematically with mother's ethnicity, age, or education or with child's birth weight, gender, or neonatal health status; but they were positively related to children's IQ scores at age 3. Only 1.9% of children of families in the highest tercile of participation scored in the mentally retarded range (IQ less than or equal to 70), whereas 3.5% and 13% of children in the middle and lowest participation terciles, respectively, scored in the retarded range. Similar findings were obtained for borderline intellectual functioning. These findings are consistent with previous research linking intensity of intervention services with degree of positive cognitive outcomes for high-risk infants. The determinants of variations in individual family participation remain unknown.     

Measuring time utilization in rural health centres

OBJECTIVES. During the recent re-design of the primary health care system in Cameroon a time-motion study was undertaken to determine how health workers at rural health centres use their time before redefining their roles. METHODS. The study developed a simple, effective and inexpensive tool which uses the activity sampling technique, and was applied to 20 health centres with a total of 19,080 observations being made of 64 health workers who represented all grades of worker in the government health services. RESULTS. The study developed a clear picture of how health centre staff apportion their time, and how the division of labour and tasks is carried out in a rural health centre. It found that only 27% of health workers' time is currently being spent on productive, health-related activities, and of this time, the largest proportion is spent on curative, clinical work. Less than 1% of health workers' time is spent on preventive and outreach activities. DISCUSSION. This study has developed a simple and inexpensive tool which can be used in any health facility to determine how health-related activities are carried out. This is an important step if changes in the delivery structure are to be made, because it establishes the discrepancy between expected and actual behaviour, and provides an important baseline for the evaluation of the effectiveness of any changes that are introduced within the system.     

Changes in Canadian women''s mammography rates since the implementation of mass screening programs.

OBJECTIVES: This study reports on Canadian mammography rates between 1990, when mass screening programs were launched, and 1994/95. METHODS: Mammography rates from 2 national surveys were compared according to the presence of a provincial screening program. RESULTS: Mammography rates among women aged 50 to 69 years (the targeted group) increased significantly, by 16%; increases were twice as high in provinces with screening programs. Among women in their 40s (nontargeted group), the changes were insignificant and independent of screening program status. CONCLUSIONS: Screening programs appear to have influenced the mammography rates of targeted women aged 50 to 69 years.     

Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review

The prediction of drug-target interactions (DTIs) is of extraordinary significance to modern drug discovery in terms of suggesting new drug candidates and repositioning old drugs. Despite technological advances, large-scale experimental determination of DTIs is still expensive and laborious. Effective and low-cost computational alternatives remain in strong need. Meanwhile, open-access resources have been rapidly growing with massive amount of bioactivity data becoming available, creating unprecedented opportunities for the development of novel in silico models for large-scale DTI prediction. In this work, we review the state-of-the-art computational approaches for identifying DTIs from a data-centric perspective: what the underlying data are and how they are utilized in each study. We also summarize popular public data resources and online tools for DTI prediction. It is found that various types of data were employed including properties of chemical structures, drug therapeutic effects and side effects, drug-target binding, drug-drug interactions, bioactivity data of drug molecules across multiple biological targets, and drug-induced gene expressions. More often, the heterogeneous data were integrated to offer better performance. However, challenges remain such as handling data imbalance, incorporating negative samples and quantitative bioactivity data, as well as maintaining cross-links among different data sources, which are essential for large-scale and automated information integration.