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Bird Diversity Relative to Forest Types and Physical Factors at Tung Salang Luang National Park, Thailand
Auttpol Nakwa,Narit Sitasuwan,Araya Jatisatein,Porntip Chantaramongkol,Wasun Pupichit,Pornchai Srisakb
Research Journal of Biological Sciences , 2012,
Abstract: A survey of bird diversity was carried out at Tung Salang Luang National Park in three forest types i.e. mixed forest (seasonal evergreen forest mixed with deciduous dipterocarp forest), seasonal evergreen forest and deciduous dipterocarp forest, during March 2004 to February 2005. The point count mixed line transect methods were used for data collection. The survey found 6,697 birds in total from 140 sp., 35 families and 11 orders occurring in the mixed forest, seasonal evergreen forest and deciduous dipterocarp forest were as follows: 107, 100 and 94 sp. The quantitative bird communities have a negative correlation with climatic changes, as a result, the dynamic pattern of bird populations in the 3 habitats during a year were similar. The fewest species numbers and individual numbers were found during the rainy season and slightly high during the late rainy to early cool seasons. The highest bird populations were found during cool season. Similarity index values of birds in both mixed forest and seasonal evergreen forest were the greatest similar, while both mixed forest and deciduous dipterocarp forest were fewest less similar. The 72.6-78.3% qualitative similarity index values of bird species between study sites was done. Mixed forest had the highest Shannon diversity index 3.9507, followed by deciduous dipterocarp and seasonal evergreen forest were 3.6387 and 3.6025, respectively. The pattern observed suggest that the structure and dynamics of the Tung Salang Luang bird community are strongly liked to physical factors and habitat heterogeneity. Two particular species of bird were observed in this study: Aviceda jerdoni (Jerdon` Baza) and Coracina javensis (Javan Cuckooshrike).
Prevalence of genotypic HIV-1 drug resistance in Thailand, 2002
Ekachai Jenwitheesuk, Chotip Watitpun, Asda Vibhagool, Wasun Chantratita
Annals of Clinical Microbiology and Antimicrobials , 2003, DOI: 10.1186/1476-0711-2-4
Abstract: Genotypic resistance testing was performed on samples collected in 2002 from 88 HIV-1 infected individuals. Automated DNA sequencing was used to genotype the HIV-1 polymerase gene isolated from patients' plasma.Resistance to protease inhibitors, nucleoside and non-nucleoside reverse transcriptase inhibitors were found in 10 (12%), 42 (48%) and 19 (21%) patients, respectively. The most common drug resistance mutations in the protease gene were at codon 82 (8%), 90 (7%) and 54 (6%), whereas resistant mutations at codon 215 (45%), 67 (40%), 41 (38%) and 184 (27%) were commonly found in the RT gene. This finding indicates that genotypic resistance to nucleoside reverse transcriptase inhibitors was prevalent in 2002. The frequency of resistant mutations corresponding to non-nucleoside reverse transcriptase inhibitors was three times higher-, while resistant mutation corresponding to protease inhibitors was two times lower than those frequencies determined in 2001.This study shows that the frequencies of RT inhibitor resistance mutations have been increased after the reduction in the price of RT inhibitors since December 2001. We believe that this was an important factor that influenced the mutation patterns of HIV-1 protease and RT genes in Thailand.During the last decade, the prevalence of human immunodeficiency virus type 1 (HIV-1) drug resistance has increased in developed countries as a result of widespread antiretroviral therapy [1-9]. Genotypic evidence of resistance for any drug was found in fewer than 2% of cases in one study from 1989 [4], increased to 10%-16% in cohorts recruited after 1995 [2,3], and attained between 20% and 26% in studies performed since 1997 [5-9]. Overall, several studies show rates of primary genotypic drug resistance between 10% and 18% for nucleoside reverse transcriptase inhibitors (NRTIs), of none to 13% for non-nucleoside reverse transcriptase inhibitors (NNRTIs), and of 3% to 7% for protease inhibitors (PIs) [1-9].In July 2002, S Sir
ParallABEL: an R library for generalized parallelization of genome-wide association studies
Unitsa Sangket, Surakameth Mahasirimongkol, Wasun Chantratita, Pichaya Tandayya, Yurii S Aulchenko
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-217
Abstract: Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors.Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.GWA analysis [1] is a well established and powerful method for identifying loci associated with variations of c
Genome-Wide Association Study in Thai Tsunami Survivors Identified Risk Alleles for Posttraumatic Stress Disorder  [PDF]
Nuntika Thavichachart, Taisei Mushiroda, Thongchai Thavichachart, Ongart Charoensook, Anchalee Prasansuklab, Prathan Rutchatajumroon, Sookjaroen Tangwongchai, Puangsoi Worakul, Buranee Kanchanatawan, Siriluck Suppapitiporn, Atapol Sughondhabirom, Chutima Roomruangwong, Wasun Chantratita, Atsushi Takahashi, Michiaki Kubo, Naoyuki Kamatani, Yusuke Nakamura
Open Journal of Genetics (OJGen) , 2015, DOI: 10.4236/ojgen.2015.52004
Abstract: Posttraumatic stress disorder (PTSD) is a psychiatric disorder found in individuals afflicted by a traumatic event. Multiple environmental and genetic factors can contribute to PTSD susceptibility. Since it is rare to find members of the same family afflicted by the same catastrophic event, it is not practical to determine PTSD susceptibility genes by a gene linkage analysis. A natural disaster, such as the 2004 Tsunami, provided us with a rare chance for a genetic analysis of PTSD. To identify SNPs associated with PTSD susceptibility, we conducted a genome-association study (GWAS) in Thai-Tsunami survivors. Initial phase of the study with 396 chronic PTSD patients and 457 controls, we identified top ninety SNPs (P < 1 × 10-4), which were further assessed in the second phase with 395 chronic PTSD patients and 798 controls. Two SNPs (rs267950 and rs954406), were identified in the second phase, and subjected to fine mapping using a data set from both phases. SNP rs267943 showed the strongest association with PTSD susceptibility and was in complete linkage disequilibrium with SNP rs267950 with P = 6.15 × 10-8, OR = 1.46 and 95% CI = 1.19 - 1.79, reaching genome-wide significance. SNP rs267943 is located on chromosome 5 in the intron of the death-associated protein 1 (DAP1) gene and, when linked to a synthetic promoter, could regulate transcription. To our knowledge, this is the first GWAS for PTSD susceptibility in an Asian population which could provide an important insight into the genetic contribution of PTSD and may lead to new treatment strategies for PTSD.
Influence of DAP1 Genotype and Psychosocial Factors on Posttraumatic Stress Disorder in Thai Tsunami Survivors: A GxE Approach  [PDF]
Nuntika Thavichachart, Prathan Rutchatajumroon, Taisei Mushiroda, Anchalee Prasansuklab, Sookjaroen Tangwongchai, Puangsoi Worakul, Buranee Kanchanatawan, Siriluck Suppapitiporn, Atapol Sughondhabirom, Chutima Roomruangwong, Ongart Charoensook, Wasun Chantratita, Atsushi Takahashi, Michiaki Kubo, Naoyuki Kamatani, Yusuke Nakamura
Open Journal of Genetics (OJGen) , 2019, DOI: 10.4236/ojgen.2019.93005
Abstract: Background: Posttraumatic Stress Disorder (PTSD) is a psychiatric disorder found in individuals afflicted by a traumatic event including the natural disaster. “Tsunami” occurred in Andaman coast of Thailand on December 26, 2004, in which 33.6% of survivors were diagnosed as PTSD. This study aimed to explore the single nucleotide polymorphism (SNP). rs267943 genotype is located on chromosome 5 in the intron of the death-associated protein 1 (DAP1) gene and psychosocial factors for PTSD. Methods: Participants (N = 1970) were recruited from volunteers who have complete data both of DAP1 gene and psychosocial factor. Results: Using a binary logistic regression model, significant gene-environment interactions were found for the single nucleotide polymorphism (SNP) rs267943 and psychosocial factors including depression (adj. OR = 6.0, 95% CI = 4.29 - 8.39), neurotic personality (adj. OR = 2.73, 95% CI = 2.18 - 3.42), planning (adj. OR = 1.52, 95% CI = 1.20 - 1.93), use of emotional support (adj. OR = 1.32, 95% CI = 1.21 - 1.94) with statistical significant p < 0.001 and self-distraction (adj. OR = 1.52, 95% CI = 1.15 - 1.85) with statistical significant p < 0.05. Conclusion: This study demonstrated that GxE studies can be utilized to shed light on the origins of PTSD.
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