11,503 research outputs found
Reducing Bias of Allele Frequency Estimates by Modeling SNP Genotype Data with Informative Missingness
The presence of missing single-nucleotide polymorphism (SNP) genotypes is common in genetic studies. For studies with low-density SNPs, the most commonly used approach to dealing with genotype missingness is to simply remove the observations with missing genotypes from the analyses. This naïve method is straightforward but is valid only when the missingness is random. However, a given assay often has a different capability in genotyping heterozygotes and homozygotes, causing the phenomenon of “differential dropout” in the sense that the missing rates of heterozygotes and homozygotes are different. In practice, differential dropout among genotypes exists in even carefully designed studies, such as the data from the HapMap project and the Wellcome Trust Case Control Consortium. Under the assumption of Hardy–Weinberg equilibrium and no genotyping error, we here propose a statistical method to model the differential dropout among different genotypes. Compared with the naïve method, our method provides more accurate allele frequency estimates when the differential dropout is present. To demonstrate its practical use, we further apply our method to the HapMap data and a scleroderma data set
Assessment of timber value and carbon credits provided by pure and mixed forests in Taiwan
IntroductionClear-cutting an even-aged pure forest is a conventional forest operation for wood production. However, this type of operation is unsuitable for sustainable management with multiple disadvantages. By contrast, mixed forests are a forestation strategy that accommodates diversity. This study aims to assess and compare the timber value and carbon credits of a pure forest and a mixed forest, which is transformed from a pure forest. Two alternative options in managing plantations of pure forest (with Cryptomeria japonica) and mixed forest (with part of C. japonica cut and Cinnamomum camphora replanted) are evaluated considering both timber value and carbon credits. Scenarios with various harvesting intensities and carbon payments were also considered.MethodA theoretical model was applied, converting pure forest into mixed forest, then two species are cut or replanted in the second round. By contrast, in the pure forest situation, the setting for the second rotation period is a pure forest for 20 years. The model was applied in a simulation experiment and the study area is Taiwan. The selected tree species are representative and have been chosen for analysis.ResultsThis study showed that even-aged pure forests had higher wood sales and lower carbon payments than uneven-aged mixed forests. The net present value from market value would be from −255,403 NTD ha−1 to −74,134 NTD ha−1 and that from carbon value will be from 156,076 NTD ha−1 to 208,937 NTD ha−1.DiscussionThis study showed strategies by which values could be increased during the transition from an even-aged pure forest to a mixed forest. Feasible methods included reducing the costs of reforestation, management, and cutting while increasing carbon prices to increase profits from wood and carbon income. A higher harvesting intensity could contribute to greater production and increase the area available for planting, resulting in greater profits from wood and carbon income
STI571 reduces TRAIL-induced apoptosis in colon cancer cells: c-Abl activation by the death receptor leads to stress kinase-dependent cell death
<p>Abstract</p> <p>Background</p> <p>In an effort to achieve better cancer therapies, we elucidated the combination cancer therapy of STI571 (an inhibitor of Bcr-Abl and clinically used for chronic myelogenous leukemia) and TNF-related apoptosis-inducing ligand (TRAIL, a developing antitumor agent) in leukemia, colon, and prostate cancer cells.</p> <p>Methods</p> <p>Colon cancer (HCT116, SW480), prostate cancer (PC3, LNCaP) and leukemia (K562) cells were treated with STI571 and TRAIL. Cell viability was determined by MTT assay and sub-G1 appearance. Protein expression and kinase phosphorylation were determined by Western blotting. c-Abl and p73 activities were inhibited by target-specific small interfering (si)RNA. In vitro kinase assay of c-Abl was conducted using CRK as a substrate.</p> <p>Results</p> <p>We found that STI571 exerts opposite effects on the antitumor activity of TRAIL. It enhanced cytotoxicity in TRAIL-treated K562 leukemia cells and reduced TRAIL-induced apoptosis in HCT116 and SW480 colon cancer cells, while having no effect on PC3 and LNCaP cells. In colon and prostate cancer cells, TRAIL caused c-Abl cleavage to the active form via a caspase pathway. Interestingly, JNK and p38 MAPK inhibitors effectively blocked TRAIL-induced toxicity in the colon, but not in prostate cancer cells. Next, we found that STI571 could attenuate TRAIL-induced c-Abl, JNK and p38 activation in HCT116 cells. In addition, siRNA targeting knockdown of c-Abl and p73 also reduced TRAIL-induced cytotoxicity, rendering HCT116 cells less responsive to stress kinase activation, and masking the cytoprotective effect of STI571.</p> <p>Conclusions</p> <p>All together we demonstrate a novel mediator role of p73 in activating the stress kinases p38 and JNK in the classical apoptotic pathway of TRAIL. TRAIL via caspase-dependent action can sequentially activate c-Abl, p73, and stress kinases, which contribute to apoptosis in colon cancer cells. Through the inhibition of c-Abl-mediated apoptotic p73 signaling, STI571 reduces the antitumor activity of TRAIL in colon cancer cells. Our results raise additional concerns when developing combination cancer therapy with TRAIL and STI571 in the future.</p
Increased risk of endometriosis in patients with endometritis — a nationwide cohort study involving 84,150 individuals
Objectives: To evaluate the incidence of endometriosis among endometritis patients and its association with confoundingcomorbidities.Material and methods: A population-based, retrospective cohort study of women aged between 20 to 55 years, who werenewly diagnosed with endometritis between 2000 to 2013. A total of 16,830 endometritis patients and 67,230 non-endometritisindividuals were enrolled by accessing data from the National Health Insurance Research Database of Taiwan.The comorbidities accessed were uterine leiomyoma, rheumatoid arthritis, ovarian cancer, infertility and allergic diseases.Results: The mean follow-up period was 9.15 years for the non-endometritis cohort and 9.13 years for the endometritiscohort. There were significantly higher percentages of uterine leiomyoma, rheumatoid arthritis, infertility, ovarian cancerand allergic diseases in the endometritis cohort than in the non-endometritis cohort. Patients with endometritis hada 1.5-fold increased risk of their condition advancing to endometriosis (HR 1.58, 95% CI 1.48–1.68).Conclusions: Our results suggest that patients with endometritis exhibited a positive correlation in developing endometriosis
Rare Variant Association Testing by Adaptive Combination of P-values
With the development of next-generation sequencing technology, there is a great demand for powerful statistical methods to detect rare variants (minor allele frequencies (MAFs)-MidPmethod (Cheung et al., 2012, Genet Epidemiol 36: 675–685) and propose an approach (named ‘adaptive combination of P-values for rare variant association testing’, abbreviated as ‘ADA’) that adaptively combines per-site P-values with the weights based on MAFs. Before combining P-values, we first imposed a truncation threshold upon the per-site P-values, to guard against the noise caused by the inclusion of neutral variants. ThisADA method is shown to outperform popular burden tests and non-burden tests under many scenarios. ADA is recommended for next-generation sequencing data analysis where many neutral variants may be included in a functional region
Pharmacogenomic strategy for individualizing antidepressant therapy
Despite remarkable progress, pharmacotherapy in general, including that for the treatment of depressive conditions, has often ignored the magnitude and clinical significance of the huge interindividual variations in pharmacokinetics and pharmacodynamics, resulting in poor compliance, suboptimal therapeutic effects, and treatment resistance. Advances in pharmacogenomics and computer modeling technologies hold promise for achieving the goals of “individualized” (“personalized”) medicine. However, the challenges for realizing such goals remain substantial. These include the packaging and interpretation of genotyping results, changes in medical practice (innovation diffusion), and infrasiructural, financing, ethical, and organizational issues related to the use of new information
Switchable dual-wavelength cylindrical vector beam generation from a passively mode-locked fiber laser based on carbon nanotubes
Cylindrical vector beams (CVBs) with axial symmetry in both polarization and field intensity have attracted much attention because of their unique optical properties. Conventional methods to obtain CVBs including direct modulation of light beams in free space and high-order mode excitation by offset splicing single-mode fiber (SMF) with few-mode fiber (FMF) usually works at single wavelength with rather narrow bandwidth. Here, for the first time to the best of our knowledge, we demonstrate switchable dual-wavelength CVB generation from a passively mode-locked fiber laser using carbon nanotubes (CNTs) as saturable absorber for mode-locking and a home-made mode-selective coupler (MSC) as both mode converter and birefringence filter. In experiments, the mode-locked fiber laser delivers CVB pulses of dual-wavelength (1532.5 nm, 1555.5 nm) and corresponding single wavelength with duration of hundreds of femtosecond, respectively. Moreover, the output polarization status is switchable between radially and azimuthally polarized states. The mode-locked CVBs with wavelength and polarization flexibility may have potential applications in mode-division multiplexing optical fiber communication, nanoparticle manipulation, material processing, nonlinear optics, and so on
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