Background: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-\b{eta} (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. Objectives: To disentangle the massive heterogeneities in AD progressions and identify vulnerable/critical brain regions to AD pathology. Methods: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of Alzheimer's disease (AD) progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. Results: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. Conclusion: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-\b{eta} and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of Alzheimer's disease.
Viruses invade a host through infecting and spreading among host cells. Initial virus replication and transmission are counteracted by the host innate immune response, in particular the interferon response. Although the virus-innate immune interaction has been studied in laboratory for a long time, a theoretical understanding of how the interferon response impacts on viral spread is lacking. In this work, we model this interaction as a competition process between the virus spreading and the interferon response on a two-layer multiplex network with virus and interferon spread on the two layers separately. We specifically explore how the overlap between the two layers impacts on the threshold and the final size of virus spread. A mean-field method and a general homogeneous multiplex network are adopted to approximate and analyze the behavior of system. We find that interferon response can effectively stop the spread of the virus or reduce the final size of viral infection when the two networks largely overlap each other. This is true especially when the interferon response is strong. The results provide insights about how the innate immune response counteracts viral invasion and spread. It may also have implications for designing strategies for risk mitigation in computer or social networks.
Background Allograft coronary atherosclerosis (TxCAD) is the leading cause of death after the first year after transplantation. TxCAD is believed to be a form of chronic rejection of the cardiac allografts. This study was undertaken to determine whether TxCAD could develop in the absence of a cellular alloimmune response. Methods and Results Inbred lean Zucker rats (>26 generations) served as donors and recipients of the cardiac grafts. Donor hearts were explanted at 60 or 90 days. Explanted hearts were processed for coronary artery histological analysis. Cytokine expression was determined by reverse transcription–polymerase chain reaction, and the presence of T cells within the explanted hearts was evaluated by immunohistochemistry. Forty-six transplantations were made, and TxCAD developed in all but one of the transplanted hearts. Overall, one third of the vessels examined were affected by TxCAD, and in roughly half of these vessels, the disease was severe. Native hearts were free of atherosclerosis. Interleukin-2 was absent from the transplanted hearts, and T cells were present in minimal amounts (<1 per low-power field). Conclusions TxCAD developed in the absence of a cellular alloimmune response in these genetically similar donors and recipients. The observed TxCAD was significant and comparable to what is found in rat allografting models.
Lifelong learning without catastrophic forgetting (i.e., resiliency) remains an open problem for deep neural networks. The prior art mostly focuses on convolutional neural networks. With the increasing dominance of Transformers in deep learning, it is a pressing need to study lifelong learning with Transformers. Due to the complexity of training Transformers in practice, for lifelong learning, a question naturally arises: Can Transformers be learned to grow in a task aware way, that is to be dynamically transformed by introducing lightweight learnable plastic components to the architecture, while retaining the parameter-heavy, but stable components at streaming tasks? To that end, motivated by the lifelong learning capability maintained by the functionality of Hippocampi in human brain, we explore what would be, and how to implement, Artificial Hippocampi (ArtiHippo) in Transformers. We present a method to identify, and learn to grow, ArtiHippo in Vision Transformers (ViTs) for resilient lifelong learning in four aspects: (i) Where to place ArtiHippo to enable plasticity while preserving the core function of ViTs at streaming tasks? (ii) How to represent and realize ArtiHippo to ensure expressivity and adaptivity for tackling tasks of different nature in lifelong learning? (iii) How to learn to grow ArtiHippo to exploit task synergies (i.e., the learned knowledge) and overcome catastrophic forgetting? (iv) How to harness the best of our proposed ArtiHippo and prompting-based approaches? In experiments, we test the proposed method on the challenging Visual Domain Decathlon (VDD) benchmark and the 5-Dataset benchmark under the task-incremental lifelong learning setting. It obtains consistently better performance than the prior art with sensible ArtiHippo learned continually. To our knowledge, it is the first attempt of lifelong learning with ViTs on the challenging VDD benchmark.
The clinical landscape of Peyronie's disease is everchanging. There has been growing interest in non-invasive therapeutic options that could assist patients with achieving a meaningful reduction in penile curvature without surgical intervention. These therapies are wide-ranging in terms of their mechanisms of action, efficacies, and short- and long-term safety profiles. Recently, an abundance of outcomes literature on longstanding and novel non-surgical treatment modalities has been published. For sexual medicine providers hoping to offer patients the most up-to-date and evidence-based treatments for the management of Peyronie's disease, it can be challenging to gain a thorough understanding of this body of literature. In this clinical management review, the workup and current theories on the pathophysiology of Peyronie's disease are reviewed, and the most recent outcomes data on the currently available non-surgical treatment modalities are presented. With an accurate understanding of the current landscape of Peyronie's disease treatment, sexual health providers will be able to better evaluate and engage in evidence-based shared decision-making with their patients.
Collagenase clostridium histolyticum (CCH) therapy for Peyronie's disease (PD) yields satisfaction rates of roughly 50% to 67% within 1 year of treatment completion, but little is known about long-term patient satisfaction. Our study aimed to identify clinical predictors of long-term satisfaction with CCH for PD and the impact of its side effect profile.
