HypertenGene: extracting key hypertension genes from biomedical literature with position and automatically-generated template features

<p>Abstract</p> <p>Background</p> <p>The genetic factors leading to hypertension have been extensively studied, and large numbers of research papers have been published on the subject. One of hypertension researchers' primary research tasks is to locate key hypertension-related genes in abstracts. However, gathering such information with existing tools is not easy: (1) Searching for articles often returns far too many hits to browse through. (2) The search results do not highlight the hypertension-related genes discovered in the abstract. (3) Even though some text mining services mark up gene names in the abstract, the key genes investigated in a paper are still not distinguished from other genes. To facilitate the information gathering process for hypertension researchers, one solution would be to extract the key hypertension-related genes in each abstract. Three major tasks are involved in the construction of this system: (1) gene and hypertension named entity recognition, (2) section categorization, and (3) gene-hypertension relation extraction.</p> <p>Results</p> <p>We first compare the retrieval performance achieved by individually adding template features and position features to the baseline system. Then, the combination of both is examined. We found that using position features can almost double the original AUC score (0.8140vs.0.4936) of the baseline system. However, adding template features only results in marginal improvement (0.0197). Including both improves AUC to 0.8184, indicating that these two sets of features are complementary, and do not have overlapping effects. We then examine the performance in a different domain--diabetes, and the result shows a satisfactory AUC of 0.83.</p> <p>Conclusion</p> <p>Our approach successfully exploits template features to recognize true hypertension-related gene mentions and position features to distinguish key genes from other related genes. Templates are automatically generated and checked by biologists to minimize labor costs. Our approach integrates the advantages of machine learning models and pattern matching. To the best of our knowledge, this the first systematic study of extracting hypertension-related genes and the first attempt to create a hypertension-gene relation corpus based on the GAD database. Furthermore, our paper proposes and tests novel features for extracting key hypertension genes, such as relative position, section, and template features, which could also be applied to key-gene extraction for other diseases.</p

Effect of Temperature Gradient Direction in the Catalyst Nanoparticle on CNTs Growth Mode

To improve the understanding on CNT growth modes, the various processes, including thermal CVD, MP-CVD and ECR-CVD, have been used to deposit CNTs on nanoporous SBA-15 and Si wafer substrates with C2H2 and H2 as reaction gases. The experiments to vary process parameter of ΔT, defined as the vector quantities of temperature at catalyst top minus it at catalyst bottom, were carried out to demonstrate its effect on the CNT growth mode. The TEM and TGA analyses were used to characterize their growth modes and carbon yields of the processes. The results show that ΔT can be used to monitor the temperature gradient direction across the catalyst nanoparticle during the growth stage of CNTs. The results also indicate that the tip-growth CNTs, base-growth CNTs and onion-like carbon are generally fabricated under conditions of ΔT > 0, <0 and ~0, respectively. Our proposed growth mechanisms can be successfully adopted to explain why the base- and tip-growth CNTs are common in thermal CVD and plasma-enhanced CVD processes, respectively. Furthermore, our experiments have also successfully demonstrated the possibility to vary ΔT to obtain the desired growth mode of CNTs by thermal or plasma-enhanced CVD systems for different applications

Laser Interactions for the Synthesis and In Situ Diagnostics of Nanomaterials

Laser interactions have traditionall been at thec center of nanomaterials science, providing highly nonequilibrium growth conditions to enable the syn- thesis of novel new nanoparticles, nanotubes, and nanowires with metastable phases. Simultaneously, lasers provide unique opportunities for the remote char- acterization of nanomaterial size, structure, and composition through tunable laser spectroscopy, scattering, and imaging. Pulsed lasers offer the opportunity, there- fore, to supply the required energy and excitation to both control and understand the growth processes of nanomaterials, providing valuable views of the typically nonequilibrium growth kinetics and intermediates involved. Here we illustrate the key challenges and progress in laser interactions for the synthesis and in situ diagnostics of nanomaterials through recent examples involving primarily carbon nanomaterials, including the pulsed growth of carbon nanotubes and graphene