Adiponectin protects against paraquat-induced lung injury by attenuating oxidative/nitrative stress.

The specific mechanisms underlying paraquat (PQ)-induced lung injury remain unknown, which limits understanding of its cytotoxic potential. Although oxidative stress has been established as an important mechanism underlying PQ toxicity, multiple antioxidants have proven ineffective in attenuating the deleterious effects of PQ. Adiponectin, which shows anti-oxidative and antinitrative effects, may have the potential to reduce PQ-mediated injury. The present study determined the protective action of globular domain adiponectin (gAd) on PQ-induced lung injury, and attempted to elucidate the underlying mechanism or mechanisms of action. BALB/c mice were administered PQ, with and without 12 or 36 h of gAd pre-treatment. The pulmonary oxidative/nitrative status was assessed by measuring pulmonary O2(•-), superoxide dismutase (SOD), malondialdehyde (MDA), nitric oxide (NO) and 8-hydroxy-2-dydeoxy guanosine (8-OHdG) production, and blood 3-Nitrotyrosine (3-NT). At a dose of 20 mg/kg, PQ markedly increased O2(•-), SOD, MDA, NO and 8-OHdG production 3 h post-administration, but did not significantly increase 3-NT levels until 12 h. gAd inhibited these changes in a dose-dependent manner, via transient activation of MDA, followed by attenuation of MDA formation from 6 h onwards. Histological analysis demonstrated that gAd decreased interstitial edema and inflammatory cell infiltration. These results suggest that gAd protects against PQ-induced lung injury by mitigating oxidative/nitrative stress. Furthermore, gAd may be a potential therapeutic agent for PQ-induced lung injury, and further pharmacological studies are therefore warranted

An effective video processing pipeline for crowd pattern analysis

With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion “textures” from dynamic Spatio-Temporal Volume (STV) blocks formulated by live video streams has been proposed. This paper starts from introducing the common approach for STV construction and corresponding Spatio-Temporal Texture (STT) extraction techniques. Next the crowd motion information contained within the random STT slices are evaluated based on the information entropy theory to cull the static background and noises occupying most of the STV spaces. A preprocessing step using Gabor filtering for improving the STT sampling efficiency and motion fidelity has been devised and tested. The technique has been applied on benchmarking video databases for proof-of-concept and performance evaluation. Preliminary results have shown encouraging outcomes and promising potentials for its real-world crowd monitoring and control applications

A graphical simulator for modeling complex crowd behaviors

Abnormal crowd behaviors of varied real-world settings could represent or pose serious threat to public safety. The video data required for relevant analysis are often difficult to acquire due to security, privacy and data protection issues. Without large amounts of realistic crowd data, it is difficult to develop and verify crowd behavioral models, event detection techniques, and corresponding test and evaluations. This paper presented a synthetic method for generating crowd movements and tendency based on existing social and behavioral studies. Graph and tree searching algorithms as well as game engine-enabled techniques have been adopted in the study. The main outcomes of this research include a categorization model for entity-based behaviors following a linear aggregation approach; and the construction of an innovative agent-based pipeline for the synthesis of A-Star path-finding algorithm and an enhanced Social Force Model. A Spatial-Temporal Texture (STT) technique has been adopted for the evaluation of the model's effectiveness. Tests have highlighted the visual similarities between STTs extracted from the simulations and their counterparts - video recordings - from the real-world

Hydrothermally synthesized CeO2 nanowires for H2S sensing at room temperature

CeO2 nanowires were synthesized using a facile hydrothermal process without any surfactant, and their morphological, structural and gas sensing properties were systematically investigated. The CeO2 nanowires with an average diameter of 12.5 nm had a face-centered cubic fluorite structure and grew along [111] of CeO2. At the room temperature of 25 °C, hydrogen sulfide (H2S) gas sensor based on the CeO2 nanowires showed excellent sensitivity, low detection limit (50 ppb), and short response and recovery time (24 s and 15 s for 50 ppb H2S, respectively)