Improving detection of differentially expressed gene sets by applying cluster enrichment analysis to Gene Ontology

<p>Abstract</p> <p>Background</p> <p>Gene set analysis based on Gene Ontology (GO) can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment.</p> <p>Results</p> <p>We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO), to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to parent-based individual term analysis methods, the results showed that CeaGO may provide more accurate differentiation of gene expression results. When used with two acute leukemia (ALL and ALL/AML) microarray expression datasets, CeaGO correctly identified specifically enriched GO groups that were overlooked by other individual test methods.</p> <p>Conclusion</p> <p>By applying CeaGO to both simulated and real microarray data, we showed that this approach could enhance the interpretation of microarray experiments. CeaGO is currently available at <url>http://chgc.sh.cn/en/software/CeaGO/</url>.</p

Architectural Implications of GNN Aggregation Programming Abstractions

Graph neural networks (GNNs) have gained significant popularity due to the powerful capability to extract useful representations from graph data. As the need for efficient GNN computation intensifies, a variety of programming abstractions designed for optimizing GNN Aggregation have emerged to facilitate acceleration. However, there is no comprehensive evaluation and analysis upon existing abstractions, thus no clear consensus on which approach is better. In this letter, we classify existing programming abstractions for GNN Aggregation by the dimension of data organization and propagation method. By constructing these abstractions on a state-of-the-art GNN library, we perform a thorough and detailed characterization study to compare their performance and efficiency, and provide several insights on future GNN acceleration based on our analysis.Comment: 4 pages, to be published in IEEE Computer Architecture Letters (CAL

Association between Single Nucleotide Polymorphisms in SIRT1 and SIRT2 Loci and Growth in Tibetan Sheep

Silent information regulator 1 and 2 (SIRT1, 2) were NAD+-dependent histone or non-histone deacetylase, which emerged as key metabolic sensors in several tissues of mammals. In the present study, the search for polymorphisms within the ovine SIRT1 and SIRT2 loci as well as association analyses between SNPs and growth-related traits were performed in Tibetan sheep. To determine the expression pattern of SIRT1 and SIRT2 genes in Tibetan sheep, the quantitative real-time polymerase chain reaction (qPCR) analysis revealed that those two genes were widely expressed in diverse tissues. Expression of SIRT1 was less in abomasum of lamb, whereas it was greater in duodenum within adult stage. In the case of SIRT2, the greatest expression was observed in reticulum (lamb) and in muscle (adult), whereas the least expression was in liver for lamb and in kidney for adult animals. The association analysis demonstrated that g.3148 C \u3e T polymorphism of SIRT1 affected heart girth (p = 0.002). The g.8074 T \u3e A SNP of SIRT2 had a significant correlation with body weight (p = 0.011) and body length (p = 0.008). These findings suggested that the SIRT1 and SIRT2 polymorphism was involved in growth-related traits in Tibetan sheep, which may be considered to be genetic markers for improving the growth traits of Tibetan sheep

Scaling of Berry-curvature monopole dominated large linear positive magnetoresistance

The linear positive magnetoresistance (LPMR) is a widely observed phenomenon in topological materials, which is promising for potential applications on topological spintronics. However, its mechanism remains ambiguous yet and the effect is thus uncontrollable. Here, we report a quantitative scaling model that correlates the LPMR with the Berry curvature, based on a ferromagnetic Weyl semimetal CoS2 that bears the largest LPMR of over 500% at 2 Kelvin and 9 Tesla, among known magnetic topological semimetals. In this system, masses of Weyl nodes existing near the Fermi level, revealed by theoretical calculations, serve as Berry-curvature monopoles and low-effective-mass carriers. Based on the Weyl picture, we propose a relation $$\text{MR}=\frac{e}{\hbar }B{{\Omega }_{\text{F}}}$$, with B being the applied magnetic field and $${{\Omega }_{\text{F}}}$$ the average Berry curvature near the Fermi surface, and further introduce temperature factor to both MR/B slope (MR per unit field) and anomalous Hall conductivity, which establishes the connection between the model and experimental measurements. A clear picture of the linearly slowing down of carriers, i.e., the LPMR effect, is demonstrated under the cooperation of the k-space Berry curvature and real-space magnetic field. Our study not only provides an experimental evidence of Berry curvature induced LPMR for the first time, but also promotes the common understanding and functional designing of the large Berry-curvature MR in topological Dirac/Weyl systems for magnetic sensing or information storage

Effect of apoptosis in neural stem cells treated with sevoflurane

BACKGROUND: At present, sevoflurane inhalation anesthesia used on infants is well-known. But long-time exposure to inhalation anesthetic could cause neurologic disorder, especially nerve degeneration in infant and developing brain. The central nervous system degeneration of infants could affect the memory and cognitive function. γ-Aminobutyric acid (GABA) is a known inhibitory neurotransmitter in central nervous system. Inhalation anesthetic sevoflurane may activate GABA(A) receptor to inhibit central nervous system, leading to apoptosis of neural degeneration, cognitive dysfunction in the critical period of brain development. METHODS: Neural stem cells were derived from Wistar embryos, cultured in vitro. Third generation of neural stem cells were randomly divided into four groups according to cultured suspension: Sevoflurane group (Group S), GABA(A) receptor antagonists, Bicuculline group (Group B), Sevoflurane + GABA(A) receptor antagonists, Bicuculline group (Group S + B), dimethyl sulphoxide (DMSO) group (Group D). Group B and Group D did not receive sevoflurane preconditioning. Group S and Group S + B were pretreated with 1 minimum alveolar concentration (MAC) sevoflurane for 0 h, 3 h, 6 h, and 12 h. Group S + B and Group B were pretreated with bicuculline (10 uM). Group D was treated with DMSO (10 uL/mL). After treatments above, all groups were cultured for 48 h. Then we measured the cells viability by Cell Counting Kit (CCK-8) assay, cytotoxicity by Lactate Dehydrogenase (LDH) assay, apoptosis ratio with Annexin V/propidium iodide (PI) staining by flow cytometry, and the expression of GABA(A)R, anti-apoptotic protein Bcl-2, pro-apoptotic protein Bax and Caspase-3 by western blotting. RESULTS: After exposing to sevoflurane for 0 h, 3 h, 6 h, and 12 h with 1MAC, we found that cell viability obviously decreased and cytotoxicity increased in time-dependent way. And Annexin V/PI staining indicated increased apoptosis ratio by flow cytometry. The protein level of GABA(A) receptor, pro-apoptotic protein Bax and apoptosis protein Caspase-3 increased; while anti-apoptotic protein Bcl-2 decreased. And bicuculline could reverse all detrimental results caused by sevoflurane. CONCLUSION: Sevoflurane can inhibit the central nervous system by activating GABA(A), resulting in apoptosis of neural stem cells, thus leading to the NSCs degeneration

Measurement of the convective heat transfer coefficient of the human body in the lift-up design

So far, the research on the convective heat transfer coefficient (hc) in outdoor thermal comfort has mainly employed CFD simulation and wind tunnel experiments, which are difficult to fully restore the complex microclimate wind environment. In the traditional thermal comfort model, the influence of turbulence intensity (TI) on the hc might be underestimated. This study aims to measure the hc of the human body surface in the outdoor environment. A thermal manikin was placed in a lift-up building. The ambient wind speed ranged from 0.5m/s to 4m/s, with the TI ranging from 4% to 55%. The experimental results show that under the same wind speed, the difference in hc between high and low TI can be up to 15%. Based on that, the regression formula for predicting hc related to wind speed and TI was proposed. This experimental study supplements the lack of field measurement of hc in outdoor thermal comfort research, which is helpful to improve the accuracy of the outdoor thermal comfort model

On the generation of full-scale urban pedestrian level wind in the wind tunnel using passive and active turbulence generators

The utilization of outdoor spaces is affected by their thermal environment. Wind, which determines the convective and evaporative heat loss from the human body, is one of the most influencing factors of thermal comfort. In the prevailing outdoor thermal comfort models, the convective heat transfer coefficients were pre-measured on a thermal manikin in a wind tunnel, where the wind speed was mostly stable. However, field measurements suggested that a typical outdoor wind process over complex terrains, like urban landscapes, are generally non-stationary. There is no experimental data on how the misrepresentation of wind may affect the convective heat transfer prediction for outdoor thermal comfort prediction. This study simulates urban pedestrian-level wind patterns in a wind tunnel by employing active and passive turbulence generators. Results show the turbulence scale through an active gust generator is approximately one to two orders of magnitude larger than the turbulence scale through a passive grid system. The eddy length scale can be adjusted through the rotation speed of the shutters. This opens the possibility of performing studies on measuring convective heat transfer coefficient under unsteady wind conditions, similar to the real outdoor environments