Early detection of type 2 diabetes mellitus in Chinese and Indian adult population

Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

CSSI-PRO: a method for secondary structure type editing, assignment and estimation in proteins using linear combination of backbone chemical shifts

Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone H-1(alpha) and C-13' chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to alpha-helical/beta-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment.

Developing molecular diagnostics for the detection of strawberry viruses

Developing molecular diagnostics for the detection of strawberry viruses.

Sequence dependence and role of 5'-phosphate in the B to Z transition

Spectroscopic studies on pd(CG)3 and pd(GC)3 have been carried out to elucidate the sequence dependence and effect of free 5'-phosphate on the B to Z transition. Unlike d(CG)3, pd(CG)3 fails to undergo salt-induced B to Z transition at ambient temperature. Model building studies have been carried out to determine the inhibitory role of the 5'-phosphate group, but have been unsuccessful.

Detection and differentiation of bovine herpesvirus 1 and 5 using a multiplex real-time polymerase chain reaction.

A multiplex real-time PCR was developed for the detection and differentiation of two closely related bovine herpesviruses 1 (BoHV-1) and 5 (BoHV-5). The multiplex real-time PCR combines a duplex real-time PCR that targets the DNA polymerase gene of BoHV-1 and BoHV-5 and a real-time PCR targeting mitochondrial DNA, as a house-keeping gene, described previously by Cawthraw et al. (2009). The assay correctly identified 22 BoHV-1 and six BoHV-5 isolates from the Biosecurity Sciences Laboratory virus collection. BoHV-1 and BoHV-5 were also correctly identified when incorporated in spiked semen and brain tissue samples. The detection limits of the duplex assay were 10 copies of BoHV-1 and 45 copies of BoHV-5. The multiplex real-time PCR had reaction efficiencies of 1.04 for BoHV-1 and 1.08 for BoHV-5. Standard curves relating Ct value to template copy number had correlation coefficients of 0.989 for BoHV-1 and 0.978 for BoHV-5. The assay specificity was demonstrated by testing bacterial and viral DNA from pathogens commonly isolated from bovine respiratory and reproductive tracts. The validated multiplex real-time PCR was used to detect and differentiate BoHV-1 and BoHV-5 in bovine clinical samples with known histories.

Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement.

A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.

Genetic Mechanisms of Tumourigenesis in von Hippel-Lindau-Associated Tumours with the Emphasis on Capillary Hemangioblastoma

The von Hippel-lindau (VHL) disease is a dominantly inherited neoplastic disorder which predisposes patients to multiple tumours including capillary haemangioblastomas (CHBs), pheochromocytomas (PCCs), renal cell carcinomas (RCCs). CHBs are the most common manifestations of VHL disease, occurring sporadically or as a manifestation of VHL disease. Inactivation of the VHL gene at 3p25-26 is believed to cause both familial and sporadic VHL-associated tumours and germ-line mutation of the VHL gene have been detected in 100% of the CHBs studied. However, a limited number of sporadic CHBs, PCCs display VHL inactivation. Other molecular alterations involved in tumourigenesis of sporadic CHBs, PCCs remain largely unknown. The purpose of the present work was to search for genetic alterations, or other mechanisms of inactivation, in addition to the VHL gene, that may be important in the development of VHL-associated tumours. Though less satisfactory than cure, prevention and early detection are the most promising and feasible means reducing cancer morbidity and mortality. This work is based on the view that increasing knowledge about the molecular events underlying tumour development will eventually aid in early detection and lead to improved treatment. We evaluated a large set of VHL-associated patients, searched for a clinical and radiologic signs of the disease. We succesfully performed a germ-line mutation analysis and characterised three patient groups, VHL, suspect VHL and sporadic, a germ-line mutation analysis revealed a 50% mutation rate only in the VHL groups, no sporadic or suspect cases displayed any mutation. We also utilized comparative genomic hybridization (CGH) to screen for DNA copy number changes in both sporadic and VHL-associated CHB. Our analysis revealed (27%) DNA copy number losses. The most common finding was loss of chromosomal arm 6q, seen in (23%) cases, No differences were noted between VHL-associated and sporadic tumours. Furthermore a loss of heterozygosity (LOH) study on chromosome 3p and 6q was done with the purpose to determine allele losses not observable by CGH, and to uncover the location of putative tumour suppressor genes important in CHB and PCC tumourigenesis. We identified loss of chromosome 6q and a minimal deleted area at 6q23-24 in CHBs. We also showed LOH at 6q23-24 in PCCs and identified the ZAC1 (6q24-25) as a candidate gene, ZAC1 is a maternally imprinted tumour suppressor gene with anti proliferative properties. To study further the role of ZAC inactivation in CHBs, we investigated LOH, promoter hypermethylation and expression status of the ZAC1 gene in mainly sporadic CHBs. Our LOH analysis revealed that the majority of the tumours with allele loss. The gene promoter methylation analysis similarly detected predominance of the methylated ZAC sequence in almost all tumours. Immunohistochemistry exhibited a strongly reduced expression of ZAC in stromal cells of all CHBs studied. Our current results indicate that the absence of the unmethylated, ZAC1 promoter sequence was highly concurrent with LOH for the ZAC1 region or 6q loss. This observation together with lack of ZAC expression, points to preferential loss of the non imprinted, expressed ZAC allele in CHB, in summary, our series of studies reveal a new chromosomal region 6q, emphasizes the importance of ZAC1 gene in the development of CHB and PCC, particularly in non-VHL associated cases.

Dengue virus infection : Diagnostics and molecular epidemiology

Dengue is a mosquito-borne viral disease caused by the four dengue virus serotypes (DENV-1-4) and is currently considered as the most important arthropod-borne viral disease in the world. Nearly half of the human population lives in risk areas, and 50-100 million infections occur yearly according to World Health Organization. The disease can vary from a mild febrile disease to severe haemorrhagic fever and shock. A secondary infection with heterologous serotype increases the risk for severe disease outcome. During the last three decades the impact of dengue has dramatically increased in the endemic areas including the tropics and subtropics of the world. The current situation with massive epidemics of severe disease forms has been associated with socio-ecological changes that have increased the transmission and enabled the co-circulation of different serotypes. Consequently, an increase of dengue has also been observed in travelers visiting these areas. Currently approximately 30 cases are diagnosed yearly in Finnish travelers. In travelers dengue is rarely a life-threatening disease, however in the current study, a fatality was documented in a young Finnish patient who experienced a prolonged primary dengue infection. To improve particularly early laboratory diagnostics, a novel real-time RT-PCR method was developed for the detection of DENV-1-4 RNA based on TaqMan chemistry. The method was shown to be sensitive and specific for detecting DENV RNA and suitable for diagnostic use. The newly developed real-time RT-PCR was compared to other available early diagnostic methods including IgM and NS1 antigen detection using a panel of selected patient samples. The results suggest that the best diagnostic rates are achieved by a combination of IgM with RNA or NS1 detection. The dengue virus strains studied here included the first DENV strains isolated from serum samples of Finnish travelers collected in 2000-2005. The results of sequence analysis demonstrated that the 11 isolates included all four DENV serotypes and presented a global sample of DENV strains from different geographical areas including Asia, Africa and South America. In the present study sequence analysis was also carried out for a collection of 23 novel DENV-2 isolates from Venezuelan patients collected in 1999-2005. The Venezuelan DENV-2 exclusively represented the American-Asian genotype, suggesting that no foreign DENV-2 lineages have recently been introduced to the country. The results also suggest that the DENV-2 viruses detected earlier from Venezuela have been maintained in the area where they have evolved into several lineages. This is in contrast to the pattern observed in some other dengue endemic areas, where introductions of novel virus types and lineages are frequently detected.

Sequence generator for periodic sampling of transient phenomena

A simple instrument that can provide a sequence of timed pulses for first initiating a transient process and then enabling sampling and recording periodically during the course of the transient event is described. The time delay between the first of these sampling pulses and the start of the transient event is adjustable. This sequence generator has additional features that make it ideal for use in acquiring the waveforms when a storage oscilloscope is used as the recording device. For avoiding the clutter caused by many waveforms being recorded at the same place on an oscilloscope screen such features as displacements of waveforms in the X and Y directions and trace blanking at places where the waveform is not required, have been incorporated. This sequence generator has been employed to acquire a sequence of Raman scattered radiation signals from an adiabatically expanding saturated vapour probed by a flashlamp-pumped dye laser.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.