The protective role of pregnane X receptor in lipopolysaccharide/D-galactosamine-induced acute liver injury.

The pregnane X receptor (PXR) is a nuclear receptor transcription factor regulating drug-metabolizing enzymes and transporters that facilitate xenobiotic and endobiotic detoxification. Recent studies show that PXR is important in abrogating intestinal tissue damage. This study examines the role of PXR in lipopolysaccharide (LPS)/D-galactosamine (GalN)-induced acute liver injury using wild-type and PXR-null mice. LPS/GalN-treated PXR-null mice had greater increases of alanine transaminase (ALT), hepatocyte apoptosis, necrosis, and hemorrhagic liver injury than wild-type mice. LPS/GalN-mediated phosphorylation of JNK1/2 and ERK1/2 was differentially regulated in wild-type and PXR-null mice. Importantly, LPS/GalN-induced hepatic Stat3 survival signaling was impaired and early activation of Jak2 was delayed in PXR-null mice. Expression levels of pro-survival proteins Bcl-xL and heme oxygenase-1 (HO-1), which are downstream of Stat3, were substantially lower in PXR-null than wild-type mouse livers after LPS/GalN treatment. Autophagy is also involved in LPS/GalN-induced liver injury. Lack of PXR resulted in a significant reduction of LC3B-I, -II as well as Beclin-1 protein levels after LPS/GalN treatment. In addition, PXR is implicated in hepatocytes homeostasis. Taken together, PXR is a critical hepatoprotective factor. Increases of LPS/GalN-induced hepatocyte apoptosis and liver injury in PXR-null mice are due to deregulated mitogen-activated protein (MAP) kinase activation as well as delayed Jak2/Stat3 activation, which lead to a compromise in defense mechanisms that involve Bcl-xL-, HO-1, and autophagy-mediated pathways

Multiple Object Tracking with Correlation Filters and Deep Features

This thesis studies on-line multiple object tracking (MOT) problem which has been developed in numerous real-world applications, such as emerging self-driving car agents or estimating a target's trajectory over time to identify its movement pattern. The challenges that an on-line MOT tracker always faces are: (1) being able to consistently and smoothly track the same target over time with the presence of occlusions, (2) being able to recover from fragmented tracks, (3) handling identity switches of the same target, and (4) being able to operate in real-time. This work aims to provide an efficient detect-and-track framework to address these challenges. To narrow down the classes of objects to be studied, but without losing the tracker's extendibility to a generic object, we pick \textit{pedestrians} as the primary objects of interest. The proposed framework consists of four building blocks, i.e. object detection, object tracking, data association, and object re-identification. While most of the MOT frameworks make the assumption of the availability of the detector in every frame, the proposed MOT tracker operates with the detector being triggered only periodically, e.g. in every three frames, leading to improved efficiency. As for each building block, the detection is performed by Single Shot Detector (SSD), which has proven efficiency and efficacy on generic object classes. When the detector is triggered and active tracks exist, data association module identifies the correspondence of the objects detected by the detector and tracked by the tracker. In cases where newly detected objects cannot be identified as any of current tracks, the re-identification module then attempts to find the correspondence for them in the history track. The experiments show that the proposed framework is outperformed by the recently published on-line MOT trackers which are based on different object detectors. However, the results suggest that the proposed framework's performance does not degrade when the detector is partially unavailable and improves in certain conditions due to better temporal consistency. Based on these experiments, we are able to identify major shortcomings of the current framework, providing possible ways to improve it and directions for the future work