Andrographolide Alleviates Acute Brain Injury in a Rat Model of Traumatic Brain Injury: Possible Involvement of Inflammatory Signaling

Neuroinflammation plays an important role in secondary injury after traumatic brain injury (TBI). Andrographolide (Andro), a diterpenoid lactone isolated from Andrographis paniculata, has been demonstrated to exhibit anti-inflammatory activity in neurodegenerative disorders. This study therefore aimed to investigate the potential neuroprotective effects of Andro after TBI and explore the underlying mechanisms. In our study, we used a weight-dropped model to induce TBI in Sprague–Dawley rats, the neurological deficits were assessed using modified neurological severity scores, Fluoro-Jade B (FJB) and terminal deoxynucleotidyl transferase (TdT) dUTP Nick-End Labeling (TUNEL) staining were employed to examine neuronal degeneration and apoptosis after TBI, immunofluorescence was designed to investigate microglial activation. Quantitative Real-time PCR and ELISA were conducted to detect the expression levels of pro-inflammatory cytokines, Western blot was used to examine the expression level of proteins of relative signaling pathway. Our results showed that after Andro administration, the neurological deficit was attenuated, and the cerebral edema and apoptosis in brain tissues were also decreased following TBI. Both microglial activation and the expression of pro-inflammatory cytokines were significantly inhibited by Andro after TBI. Moreover, Andro inhibited NF-κB p65 subunit translocation and decreased the expression levels of phosphorylated extracellular signal regulated kinase (ERK) and p38 MAPK after TBI. Altogether, this study suggests that Andro could improve neurobehavioral function by inhibiting NF-κB and MAPK signaling pathway in TBI, which might provide a new approach for treating brain injury

Intelligent Search Techniques for Large Software Systems

I would like to acknowledge the help that I have received during my research. Grateful thanks to: • Dr. Timothy Lethbridge, my supervisor, for his support, guidance, patience and intelligent comments. • The KBRE group for their help, comments, and the valuable discussions with them. • The software engineers who participated in this study. • My friends for their concerns and encouragements. • My family, for the endless support to me. ii There are many tools available today to help software engineers search in source code systems. It is often the case, however, that there is a gap between what people really want to find and the actual query strings they specify. This is because a concept in a software system may be represented by many different terms, while the same term may have different meanings in different places. Therefore, software engineers often have to guess a

A More Effective Zero-DCE Variant: Zero-DCE Tiny

The purpose of Low Illumination Image Enhancement (LLIE) is to improve the perception or interpretability of images taken in low illumination environments. This work inherits the work of Zero-Reference Deep Curve Estimation (Zero-DCE) and proposes a more effective image enhancement model, Zero-DCE Tiny. First, the new model introduces the Cross Stage Partial Network (CSPNet) into the original U-net structure, divides basic feature maps into two parts, and then recombines it through the structure of cross-phase connection to achieve a richer gradient combination with less computation. Second, we replace all the deep separable convolutions except the last layer with Ghost modules, which makes the network lighter. Finally, we introduce the channel consistency loss into the non-reference loss, which further strengthens the constraint on the pixel distribution of the enhanced image and the original image. Experiments show that compared with Zero-DCE++, the network proposed in this work is more lightweight and surpasses the Zero-DCE++ method in some important image enhancement evaluation indexes

A More Effective Zero-DCE Variant: Zero-DCE Tiny

The purpose of Low Illumination Image Enhancement (LLIE) is to improve the perception or interpretability of images taken in low illumination environments. This work inherits the work of Zero-Reference Deep Curve Estimation (Zero-DCE) and proposes a more effective image enhancement model, Zero-DCE Tiny. First, the new model introduces the Cross Stage Partial Network (CSPNet) into the original U-net structure, divides basic feature maps into two parts, and then recombines it through the structure of cross-phase connection to achieve a richer gradient combination with less computation. Second, we replace all the deep separable convolutions except the last layer with Ghost modules, which makes the network lighter. Finally, we introduce the channel consistency loss into the non-reference loss, which further strengthens the constraint on the pixel distribution of the enhanced image and the original image. Experiments show that compared with Zero-DCE++, the network proposed in this work is more lightweight and surpasses the Zero-DCE++ method in some important image enhancement evaluation indexes

Serum Lipids and Breast Cancer Risk: A Meta-Analysis of Prospective Cohort Studies

<div><p>Purpose</p><p>Epidemiologic studies exploring causal associations between serum lipids and breast cancer risk have reported contradictory results. We conducted a meta-analysis of prospective cohort studies to evaluate these associations.</p><p>Methods</p><p>Relevant studies were identified by searching PubMed and EMBASE through April 2015. We included prospective cohort studies that reported relative risk (RR) estimates with 95% confidence intervals (CIs) for the associations of specific lipid components (i.e., total cholesterol [TC], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], and triglycerides [TG]) with breast cancer risk. Either a fixed- or a random-effects model was used to calculate pooled RRs.</p><p>Results</p><p>Fifteen prospective cohort studies involving 1,189,635 participants and 23,369 breast cancer cases were included in the meta-analysis. The pooled RRs of breast cancer for the highest versus lowest categories were 0.96 (95% CI: 0.86–1.07) for TC, 0.92 (95% CI: 0.73–1.16) for HDL-C, 0.90 (95% CI: 0.77–1.06) for LDL-C, and 0.93 (95% CI: 0.86–1.00) for TG. Notably, for HDL-C, a significant reduction of breast cancer risk was observed among postmenopausal women (RR = 0.77, 95% CI: 0.64–0.93) but not among premenopausal women. Similar trends of the associations were observed in the dose-response analysis.</p><p>Conclusions</p><p>Our findings suggest that serum levels of TG but not TC and LDL-C may be inversely associated with breast cancer risk. Serum HDL-C may also protect against breast carcinogenesis among postmenopausal women.</p></div

A computational study of the aerodynamic performance of a dragonfly forewing in gliding flight

Gliding flight is a common mode of flight for dragonfly, the objective of the current research is to use numerical simulations to explore whether the corrugations have positive effect on aerodynamic performance of the dragonfly wings in gliding flight. In order to compare aerodynamic performance of the dragonfly wing and flat plate, a three-dimensional model of the dragonfly forewing and a three-dimensional flat plate with the same shape of the dragonfly forewing are established. The flow fields around three-dimensional dragonfly forewing and flat plate are simulated for Re=10000 and angles of attack changing from 0° to 25°(with an interval of 5°), numerical simulation indicate that aerodynamic performance of the dragonfly wing is slightly better than the flat plate over the entire range of parameters tested, especially the effect of the corrugateions on the flow is more evident at large angle of attack