Frequency distribution of GSTM1 and GSTT1 null allele in Pakistani population and risk of disease incidence

2010 ◽  
Vol 30 (1) ◽  
pp. 76-79 ◽  
Author(s):  
Rehan Sadiq Shaikh ◽  
Muhammad Amir ◽  
Ahmed Ijaz Masood ◽  
Asma Sohail ◽  
Habib-ur-Rehman Athar ◽  
...  
Gene ◽  
2012 ◽  
Vol 492 (1) ◽  
pp. 186-194 ◽  
Author(s):  
Muhammad Imran ◽  
Saqib Mahmood ◽  
Rashid Hussain ◽  
Noman B. Abid ◽  
Khalid P. Lone

2007 ◽  
Vol 97 (6) ◽  
pp. 674-683 ◽  
Author(s):  
T. R. Gottwald ◽  
R. B. Bassanezi ◽  
L. Amorim ◽  
A. Bergamin-Filho

Eradication of Asiatic citrus canker (ACC) has become increasingly difficult over the last decade, following the introduction of the Asian leafminer into Brazil and Florida, which has led to changes in the eradication protocols. The present study, undertaken in Brazil, was aimed at characterizing the spatial patterns of ACC in commercial citrus plantings to gain better understanding of the dynamics of the disease subsequent to introduction of the leafminer. The spatial patterns of ACC were mapped in 326 commercial citrus plantings and statistically assessed at various spatial dimensions. The presence of “within-group” aggregation in each plot was examined via β-binomial analysis for groups of trees parsed into three-by-three-tree quadrats. The relative intensity of aggregation was expressed as a binomial index of dispersion (D) and heterogeneity among plots expressed as the intracluster correlation coefficient, ρ. The population of data sets was found to fall into three D categories, D < 1.3, 1.3 ≤ D = 3.5, and D > 3.5. These categories then were related to other spatial characteristics. The binary form of Taylor's power law was used to assess the overdispersion of disease across plots and was highly significant. When the overall population of plots was parsed into D categories, the Taylor's R 2 improved in all cases. Although these methods assessed aggregation well, they do not give information on the number of foci or aggregations within each plot. Therefore, the number of foci per 1,000 trees was quantified and found to relate directly to the D categories. The lowest D category could be explained by a linear relationship of number of foci versus disease incidence, whereas the higher two categories were most easily explained by a generalized β function for the same relationship. Spatial autocorrelation then was used to examine the spatial relationships “among groups” composed of three-by-three-tree quadrats and determine common distances between these groups of ACC-infected trees. Aggregation was found in >84% of cases at this spatial level and there was a direct relationship between increasing D category and increasing core cluster size, and aggregation at the among-group spatial hierarchy was generally stronger for the within-row than for the across-row orientation. Clusters of disease were estimated to average between 18 and 33 tree spaces apart, and the presence of multiple foci of infection was commonplace. The effectiveness of the eradication protocol of removing all “exposed” trees within 30 m surrounding each “ACC-infected tree” was examined, and the distance of subsequent infected trees beyond this 30-m zone from the original focal infected tree was measured for each plot. A frequency distribution was compiled over all plots to describe the distance that would have been needed to circumscribe all of these outliers as a theoretical alternative protocol to the 30-m eradication protocol. The frequency distribution was well described by a monomolecular model (R2 = 0.98) and used to determine that 90, 95, and 99% of all newly infected trees occurred within 296, 396, and 623 m of prior-infected trees in commercial citrus plantings, respectively. These distances are very similar to previously reported distances determined for ACC in residential settings in Florida.


2008 ◽  
Vol 137 (5) ◽  
pp. 644-653 ◽  
Author(s):  
W.-P. SCHMIDT ◽  
B. GENSER ◽  
Z. CHALABI

SUMMARYThe measurement and analysis of common recurrent conditions such as diarrhoea, respiratory infections or fever pose methodological challenges with regard to case definition, disease surveillance and statistical analysis. In this paper we describe a flexible and robust model that can generate simulated longitudinal datasets for a range of recurrent infections, reflecting the stochastic processes that underpin the data collected in the field. It can be used to evaluate and compare alternative disease definitions, surveillance strategies and statistical methods under ‘controlled conditions’. Parameters in the model include: characterizing the distributions of the individual disease incidence and the duration of disease episodes; allowing the average disease duration to depend on an individual's number of episodes (simulating a correlation between incidence and duration); making the individual risk of disease depend on the occurrence of previous episodes (simulating autocorrelation of successive episodes); finally, incorporating seasonal variation of disease.


2008 ◽  
Vol 122 (6) ◽  
pp. 525-528 ◽  
Author(s):  
Muhammad Akram Tariq ◽  
Obaid Ullah ◽  
S. Amer Riazuddin ◽  
Sheikh Riazuddin

2021 ◽  
Author(s):  
Riffat Iqbal ◽  
Aneeqa Zafar ◽  
Arslan Habib ◽  
Maryam Mukhtar ◽  
Iram Liaqat ◽  
...  

Abstract Myocardial Infarction (MI) is the most common type of coronary heart disease characterized by pain, nausea, sweating, shortness of breath and abnormal heartbeat. Current study was conducted to identify the susceptibility of the MMP-9 gene among families affected with myocardial infarction in the Pakistani population. A family clustering study based on 5 families having MI patients was conducted. Blood samples from MI patients and their family members were collected for further genetic analysis. Patients were with a mean BMI of ±30.2 kg/m2 which indicates that obese were at high risk of disease development. The mean age for diagnosis of disease was ±50 years, in which all patients had a positive family history. Most patients were diabetic with hypertension, most of them were smokers and their exposure to air pollution was higher. Genomic DNA was isolated from the blood through manual extraction. Primers were optimized and genotyping was done by polymerase chain reaction (PCR) which was followed by DNA sequencing and restriction fragment length polymorphism (RFLP). As a result of polymorphism, A into G and C into T conversions were identified on rs17576 and rs3918242 polymorphic sites on the MMP-9 gene respectively. In conclusion smoking, hypertension, diabetes, exposure to air pollution and polymorphism of rs17576 and rs3918242 were significantly associated with the onset of MI in the Pakistani population and males were at higher risk. Further studies should be conducted on large scale to evaluate the association of MMP-9 polymorphism with MI.


Author(s):  
Johan L. Bekker ◽  
Louw C. Hoffman ◽  
Piet J. Jooste

With on-going changes in land use practices from conventional livestock farming to commercial, wildlife-based activities, the interface or interaction between livestock and wildlife is increasing. As part of the wildlife-based activities of ecotourism, breeding and hunting, game farmers are also exploring the utilisation of meat from hunted or harvested game. The expanding interface or increased interaction between livestock and wildlife increases the risk of disease incidence and the emergence of new diseases or the re-emergence of previously diagnosed diseases. The risk is not only related to domestic and wild animal health, but also to the occupational hazards that it poses to animal handlers and the consumers of game meat. This review endeavours to highlight the role that game plays in the spreading of zoonotic diseases to other animals and humans. Examples of zoonotic diseases that have occurred in wild animals in the past, their relevance and risk have been summarised and should function as a quick reference guide for wildlife veterinarians, ecologists, farmers, hunters, slaughter staff, processors and public health professionals.


2009 ◽  
Vol 29 (5) ◽  
pp. 549-556 ◽  
Author(s):  
Tanya G. K. Bentley ◽  
Milton C. Weinstein ◽  
Karen M. Kuntz

Purpose. When using continuous predictor variables in discrete-state Markov modeling, it is necessary to create categories of risk and assume homogeneous disease risk within categories, which may bias model outcomes. This analysis assessed the tradeoffs between model bias and complexity and/or data limitations when categorizing continuous risk factors in Markov models. Methods. The authors developed a generic Markov cohort model of disease, defining bias as the percentage change in life expectancy gain from a hypothetical intervention when using 2 to 15 risk factor categories as compared with modeling the risk factor as a continuous variable. They evaluated the magnitude and sign of bias as a function of disease incidence, disease-specific mortality, and relative difference in risk among categories. Results. Bias was positive in the base case, indicating that categorization overestimated life expectancy gains. The bias approached zero as the number of risk factor categories increased and did not exceed 4% for any parameter combinations or numbers of categories considered. For any given disease-specific mortality and disease incidence, bias increased with relative risk of disease. For any given relative risk, the relationship between bias and parameters such as disease-specific mortality or disease incidence was not always monotonic. Conclusions. Under the assumption of a normally distributed risk factor and reasonable assumption regarding disease risk and moderate values for the relative risk of disease given risk factor category, categorizing continuously valued risk factors in Markov models is associated with less than 4% absolute bias when at least 2 categories are used.


Author(s):  
Kyle T. Thornham ◽  
R. Jay Stipes ◽  
Randolph L. Grayson

Dogwood anthracnose, caused by Discula destructiva (1), is another new catastrophic tree disease that has ravaged natural populations of the flowering dogwood (Cornus florida) in the Appalachians over the past 15 years, and the epidemic is prognosticated to continue (2). An estimated 9.5 million acres have been affected, primarily in the Appalachian Mountains, from VA southwards, alone, and an estimated 50% of all dogwoods in PA have been killed. Since acid deposition has been linked experimentally with disease induction, and since the disease incidence and severity are more pronounced at higher elevations where lower pH precipitation events occur, we investigated the effect of acidic foliar sprays on moiphologic changes in the foliar cuticle and trichomes (3), the initial sites of infection and foci of Discula sporulation.


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