Genes and proteins controlled by cGMP-PKG during retinal degeneration

prevalence was reported as 1:3000-4000 worldwide, making it the main reason for blindness in the working population in industrial countries. The mutations of over 70 genes have been related to this genetic disorder, and there is generally no effective treatment, except for gene therapy for the RPE65 mutations. Hence, new molecular targets are required for novel treatment development. The signaling molecule cGMP and its dependent protein kinase G (cGMP-PKG) have been regarded as one of theprime effectors to drive the disease. However, the insights into the downstream signaling of the system, are still unclear. This thesis aimed to explore the cGMP-PKG-dependent transcriptome and proteome.The Paper I showed the cGMP-PKG-dependent transcriptome in this study. Applying RNA sequencing to study the retinal explants from the diseased rd1 models and WT with cGMP-PKG manipulation, I identified the cGMP-PKG-dependent genes and proposed that this system may negatively regulate oxidative phosphorylation and mitochondrial pathways, which may affect retinal degeneration.The paper II investigated the cGMP-PKG phosphoproteome. The phosphorylated peptide enrichment and mass-spectrometry were applied to explore the cGMP-PKG-dependent phosphoproteome within rd1 retinal explants with PKG inhibition or not. I identified a list of cGMP-PKG-dominated phosphorylations and picked up RAF1 proto-oncogene, serine/threonine kinase (RAF1) for further validation. This suggested that RAF1 may be involved in retinal degeneration, although in an as yet unclear mechanism.The Paper III investigated cGMP-PKG-dependent kinase activity profiling and the phosphoproteome with a microarray-based technique and mass-spectrometry, respectively. The rd10 model, with a different mutation in the gene for PDE6 was used. This yielded the lists of cGMP-PKG-dependent kinase and phosphorylations, which were partially compatible with Paper II. Also, this showed that Ca2+/calmodulindependent protein kinase II and IV (CaMK2, CaMK4) may play a role during retinal degeneration.Paper IV focused on cyclin-dependent kinase 1 (CDK1), which was identified from Paper II, namely, and investigated if it has effects on retinal degeneration. The data showed that CDK1 participates in the late stage of retinal degeneration, and also provided a link between this enzyme and the cGMP-PKG system.The Paper V validated another target, pyruvate kinase isozyme M2 (PKM2) identified in the previous transcriptome study. The PKM2 within retinas was activated from two disease models, namely rd2 and rd10 in a pharmacological manner during explant culture. I observed that PKM2 activation in rd10 alleviated the photoreceptor degeneration while no difference was noticed in rd2 under treatment.All in all, this thesis provides novel insights about cGMP-PKG-dependent targets, which may have a role during photoreceptor degeneration and cast light on the therapeutic development of this retinal disease

Phase Field Characterization of Rock Fractures in Brazilian Splitting Test Specimens Containing Voids and Inclusions

The Brazilian splitting test is a widely used testing procedure for characterizing the tensile strength of natural rock or rock-like material due to the fact. However, the results of Brazilian tests on specimens with naturally existing voids and inclusions are strongly influenced by size effects and boundary conditions, while numerical modeling can assist in explaining and understanding the mechanisms. On the other hand, the potential of utilizing Brazilian test to characterize inhomogeneous deformation of rock samples with voids and inclusions of dissimilar materials still awaits to be explored. In the present study, fracture mechanisms in Brazilian discs with circular voids and filled inclusions are investigated by using the phase field model (PFM). The PFM is implemented within the framework of finite element method to study the influence of diameter, eccentricity, and quantity of the voids and inclusions on the fracture patterns and stress-strain curves. The phase field simulations can reproduce previous experimental phenomena and furthermore it deepens the understanding of the influence of inclusion and voids on the fracture pattern, overall strength and deformation behavior of inhomogeneous rock. The findings in the study highlight the potential of characterizing inhomogeneous rock through combining Brazilian tests and numerical modeling

Integrating Visual Foundation Models for Enhanced Robot Manipulation and Motion Planning: A Layered Approach

This paper presents a novel layered framework that integrates visual foundation models to improve robot manipulation tasks and motion planning. The framework consists of five layers: Perception, Cognition, Planning, Execution, and Learning. Using visual foundation models, we enhance the robot's perception of its environment, enabling more efficient task understanding and accurate motion planning. This approach allows for real-time adjustments and continual learning, leading to significant improvements in task execution. Experimental results demonstrate the effectiveness of the proposed framework in various robot manipulation tasks and motion planning scenarios, highlighting its potential for practical deployment in dynamic environments.Comment: 3 pages, 2 figures, IEEE Worksho

GeoDeformer: Geometric Deformable Transformer for Action Recognition

Vision transformers have recently emerged as an effective alternative to convolutional networks for action recognition. However, vision transformers still struggle with geometric variations prevalent in video data. This paper proposes a novel approach, GeoDeformer, designed to capture the variations inherent in action video by integrating geometric comprehension directly into the ViT architecture. Specifically, at the core of GeoDeformer is the Geometric Deformation Predictor, a module designed to identify and quantify potential spatial and temporal geometric deformations within the given video. Spatial deformations adjust the geometry within individual frames, while temporal deformations capture the cross-frame geometric dynamics, reflecting motion and temporal progression. To demonstrate the effectiveness of our approach, we incorporate it into the established MViTv2 framework, replacing the standard self-attention blocks with GeoDeformer blocks. Our experiments at UCF101, HMDB51, and Mini-K200 achieve significant increases in both Top-1 and Top-5 accuracy, establishing new state-of-the-art results with only a marginal increase in computational cost. Additionally, visualizations affirm that GeoDeformer effectively manifests explicit geometric deformations and minimizes geometric variations. Codes and checkpoints will be released.Comment: Including geometric transformations into Vi

Enhanced cGMP Interactor Rap Guanine Exchange Factor 4 (EPAC2) Expression and Activity in Degenerating Photoreceptors: : A Neuroprotective Response?

The disease retinitis pigmentosa (RP) leads to photoreceptor degeneration by a yet undefined mechanism(s). In several RP mouse models (i.e., rd mice), a high cyclic GMP (cGMP) level within photoreceptors is detected, suggesting that cGMP plays a role in degeneration. The rap guanine exchange factor 4 (EPAC2) is activated by cyclic AMP (cAMP) and is an accepted cGMP-interacting protein. It is unclear whether and how cGMP interacts with EPAC2 in degenerating photoreceptors; we therefore investigated EPAC2 expression and interactions with cGMP and cAMP in retinas of the rd1 and rd10 models for retinal degeneration. EPAC2 expression in the photoreceptor layer increased significantly during rd1 and rd10 degeneration, and an increase in EPAC2 interactions with cGMP but not cAMP in the rd1 was also seen via a proximity ligation assay on histological sections. Retinal explant cultures revealed that pharmacological inhibition of the EPAC2 activity reduced the photoreceptor layer thickness in the rd10 retina, suggesting that EPAC2 inhibition promotes degeneration. Taken together, our results support the hypothesis that high degeneration-related cGMP leads to increased EPAC2 and cGMP interactions, inhibiting EPAC2. By inference, EPAC2 could have neuroprotective capacities that may be exploited in the future

AdaFocus: Towards End-to-end Weakly Supervised Learning for Long-Video Action Understanding

Developing end-to-end models for long-video action understanding tasks presents significant computational and memory challenges. Existing works generally build models on long-video features extracted by off-the-shelf action recognition models, which are trained on short-video datasets in different domains, making the extracted features suffer domain discrepancy. To avoid this, action recognition models can be end-to-end trained on clips, which are trimmed from long videos and labeled using action interval annotations. Such fully supervised annotations are expensive to collect. Thus, a weakly supervised method is needed for long-video action understanding at scale. Under the weak supervision setting, action labels are provided for the whole video without precise start and end times of the action clip. To this end, we propose an AdaFocus framework. AdaFocus estimates the spike-actionness and temporal positions of actions, enabling it to adaptively focus on action clips that facilitate better training without the need for precise annotations. Experiments on three long-video datasets show its effectiveness. Remarkably, on two of datasets, models trained with AdaFocus under weak supervision outperform those trained under full supervision. Furthermore, we form a weakly supervised feature extraction pipeline with our AdaFocus, which enables significant improvements on three long-video action understanding tasks

A Personalized Human Drivers\u27 Risk Sensitive Characteristics Depicting Stochastic Optimal Control Algorithm for Adaptive Cruise Control

This paper presents a personalized stochastic optimal adaptive cruise control (ACC) algorithm for automated vehicles (AVs) incorporating human drivers\u27 risk-sensitivity under system and measurement uncertainties. The proposed controller is designed as a linear exponential-of-quadratic Gaussian (LEQG) problem, which utilizes the stochastic optimal control mechanism to feedback the deviation from the design car-following target. With the risk-sensitive parameter embedded in LEQG, the proposed method has the capability to characterize risk preference heterogeneity of each AV against uncertainties according to each human drivers\u27 preference. Further, the established control theory can achieve both expensive control mode and non-expensive control mode via changing the weighting matrix of the cost function in LEQG to reveal different treatments on input. Simulation tests validate the proposed approach can characterize different driving behaviors and its effectiveness in terms of reducing the deviation from equilibrium state. The ability to produce different trajectories and generate smooth control of the proposed algorithm is also verified