Circulating 25-hydroxyvitamin D concentration and cause-specific mortality in the Melbourne Collaborative Cohort Study.

Vitamin D deficiency is associated with higher all-cause mortality, but associations with specific causes of death are unclear. We investigated the association between circulating 25-hydroxyvitamin D (25(OH)D) concentration and cause-specific mortality using a case-cohort study within the Melbourne Collaborative Cohort Study (MCCS). Eligibility for the case-cohort study was restricted to participants with baseline dried blood spot samples and no pre-baseline diagnosis of cancer. These analyses included participants who died (n = 2307) during a mean follow-up of 14 years and a sex-stratified random sample of eligible cohort participants ('subcohort', n = 2923). Concentration of 25(OH)D was measured using liquid chromatography-tandem mass spectrometry. Cox regression, with Barlow weights and robust standard errors to account for the case-cohort design, was used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for cause-specific mortality in relation to 25(OH)D concentration with adjustment for confounders. Circulating 25(OH)D concentration was inversely associated with risk of death due to cancer (HR per 25 nmol/L increment = 0.88, 95 % CI 0.78-0.99), particularly colorectal cancer (HR = 0.75, 95 % CI 0.57-0.99). Higher 25(OH)D concentrations were also associated with a lower risk of death due to diseases of the respiratory system (HR = 0.62, 95 % CI 0.43-0.88), particularly chronic obstructive pulmonary disease (HR = 0.53, 95 % CI 0.30-0.94), and diseases of the digestive system (HR = 0.44, 95 % CI 0.26-0.76). Estimates for diabetes mortality (HR = 0.64, 95 % CI 0.33-1.26) and cardiovascular disease mortality (HR = 0.90, 95 % CI 0.76-1.07) lacked precision. The findings suggest that vitamin D might be important for preventing death due to some cancers, respiratory diseases, and digestive diseases

A COMPUTATAIONALLY EFFICIENT METHOD FOR ONLINE IDENTIFICATION OF TRAFFIC CONTROL INTERVENTION MEASURES

Abstract Adaptive traffic control systems such as SCOOT and SCATS are designed to respond to changes in traffic conditions and provide heuristically optimised traffic signal settings. However, these systems make gradual changes to signal settings in response to changing traffic conditions. In the EPSRC and TSB funded FREEFLOW project, a tool is being designed to rapidly identify severe traffic problems using traffic sensor data and recommend traffic signal plans and UTC parameters that have worked well in the past under similar traffic conditions for immediate implementation. This paper will present an overview of this tool, called the Intelligent Decision Support (IDS),that is designed to complement adaptive traffic control systems. The IDS is essentially a learning based system. It requires an historic database of traffic sensor data and traffic control intervention data for the application area as a knowledge base. The IDS, when deployed online, will monitor traffic sensor data to determine if the network is congested using traffic state estimation models. When IDS identifies congestion in the network, the historic database is queried for similar congestion events, where the similarity is based on both the severity and the spatial pattern of congestion. Traffic control interventions implemented during similar congestion events in the historic database are then evaluated for their effectiveness to mitigate congestion. The most effective traffic control interventions are recommended by IDS for implementation, along with an associated confidence indicator. The IDS is designed to work online against large historic datasets, and is based on traffic state estimation models developed at Imperial College London and pattern matching tools developed at the University of York. The IDS is tested offline using Inductive Loop Detector (ILD) data obtained from the ASTRID system and traffic control intervention data obtained from the UTC system at Transport for London (TfL) during its development. This paper presents the preliminary results using TfL data and outlines future research avenues in the development of IDS

Expression of interfacial Seebeck coefficient through grain boundary engineering with multi-layer graphene nanoplatelets

Expression of energy filtering to boost thermoelectric performance through grain boundary engineering utilising graphene.</p

Chemical Contamination of Green Turtle (Chelonia mydas) Eggs in Peninsular Malaysia: Implications for Conservation and Public Health

BACKGROUND: Persistent organic pollutants (POPs)-such as organochlorine pesticides (OCPS), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs)-and heavy metals have been reported in sea turtles at various stages of their life cycle. These chemicals can disrupt development and function of wildlife. Furthermore, in areas such as Peninsular Malaysia, where the human consumption of sea turtle eggs is prevalent, egg contamination may also have public health implications. OBJECTIVE: In the present study we investigated conservation and human health risks associated with the chemical contamination of green turtle (Chelonia mydas) eggs in Peninsular Malaysia. METHODS: Fifty-five C mydas eggs were collected from markets in Peninsular Malaysia and analyzed for POPs and heavy metals. We conducted screening risk assessments (SRAs) and calculated the percent of acceptable daily intake (ADI) for POPs and metals to assess conservation and human health risks associated with egg contamination. RESULTS: C mydas eggs were available in 9 of the 33 markets visited. These eggs came from seven nesting areas from as far away as Borneo Malaysia. SRAs indicated a significant risk to embryonic development associated with the observed arsenic concentrations. Furthermore, the concentrations of coplanar PCBs represented 3-300 times the ADI values set by the World Health Organization. CONCLUSIONS: The concentrations of POPs and heavy metals reported in C mydas eggs from markets in Peninsular Malaysia pose considerable risks to sea turtle conservation and human health

Carpal alignment in distal radial fractures

BACKGROUND: Carpal malalignment following the malunited distal radial fracture is described to develop as an adaptation to realign the hand to the malunion. It worsens gradually after healing of the fracture due to continued loading of the wrist. It is also reported to develop during the immobilization itself rather than after fracture healing. The present work was aimed to study the natural course and the quantitative assessment of such adaptive carpal realignment following distal radial fracture. METHODS: In a prospective study, 118 distal radial fractures treated with different modalities were followed-up with serial radiographs for a year for assessment of various radiological parameters. RESULTS: Two patterns of carpal malalignment were identified depending upon the effective radio-lunate flexion (ERLF) measured on pre-reduction radiographs. The midcarpal malalignment was seen in 98 radial fractures (83%) with the lunate following the dorsiflexed fracture fragment and a measured ERLF of less than 25°. The second pattern of radio-carpal malalignment showed the fracture fragment to dorsiflex without taking the lunate with a measured ERLF of more than 25°. The scaphoid did not follow the fracture fragment in both the patterns of malalignment. CONCLUSION: It is better to assess distal radial fractures for any wrist ligamentous injury on the post-reduction film with the restored radial anatomy than on the pre-reduction film since most carpal malalignments get corrected with the reduction of the fracture. Similar carpal malalignment reappear with the redisplacement of the fracture as seen in pre-reduction radiographs and develops during the immobilization rather than as a later compensatory mechanism for the malunion

Interleukin-6 gene amplification and shortened survival in glioblastoma patients

Interleukin-6 (IL-6) is known to promote tumour growth and survival. We evaluated IL-6 gene amplification in tumours from 53 glioma patients using fluorescence in situ hybridisation. Amplification events were detected only in glioblastomas (15 out of 36 cases), the most malignant tumours, and were significantly associated with decreased patient survival

Star forming dwarf galaxies

Star forming dwarf galaxies (SFDGs) have a high gas content and low metallicities, reminiscent of the basic entities in hierarchical galaxy formation scenarios. In the young universe they probably also played a major role in the cosmic reionization. Their abundant presence in the local volume and their youthful character make them ideal objects for detailed studies of the initial stellar mass function (IMF), fundamental star formation processes and its feedback to the interstellar medium. Occasionally we witness SFDGs involved in extreme starbursts, giving rise to strongly elevated production of super star clusters and global superwinds, mechanisms yet to be explored in more detail. SFDGs is the initial state of all dwarf galaxies and the relation to the environment provides us with a key to how different types of dwarf galaxies are emerging. In this review we will put the emphasis on the exotic starburst phase, as it seems less important for present day galaxy evolution but perhaps fundamental in the initial phase of galaxy formation.Comment: To appear in JENAM Symposium "Dwarf Galaxies: Keys to Galaxy Formation and Evolution", P. Papaderos, G. Hensler, S. Recchi (eds.). Lisbon, September 2010, Springer Verlag, in pres