Multimodal Gait Recognition for Neurodegenerative Diseases.

In recent years, single modality-based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognized that each of the established approaches has different strengths and weaknesses. As an important motor symptom, gait disturbance is usually used for diagnosis and evaluation of diseases; moreover, the use of multimodality analysis of the patient's walking pattern compensates for the one-sidedness of single modality gait recognition methods that only learn gait changes in a single measurement dimension. The fusion of multiple measurement resources has demonstrated promising performance in the identification of gait patterns associated with individual diseases. In this article, as a useful tool, we propose a novel hybrid model to learn the gait differences between three neurodegenerative diseases, between patients with different severity levels of Parkinson's disease, and between healthy individuals and patients, by fusing and aggregating data from multiple sensors. A spatial feature extractor (SFE) is applied to generating representative features of images or signals. In order to capture temporal information from the two modality data, a new correlative memory neural network (CorrMNN) architecture is designed for extracting temporal features. Afterward, we embed a multiswitch discriminator to associate the observations with individual state estimations. Compared with several state-of-the-art techniques, our proposed framework shows more accurate classification results.

Multi-View Mouse Social Behaviour Recognition With Deep Graphic Model.

Home-cage social behaviour analysis of mice is an invaluable tool to assess therapeutic efficacy of neurodegenerative diseases. Despite tremendous efforts made within the research community, single-camera video recordings are mainly used for such analysis. Because of the potential to create rich descriptions for mouse social behaviors, the use of multi-view video recordings for rodent observations is increasingly receiving much attention. However, identifying social behaviours from various views is still challenging due to the lack of correspondence across data sources. To address this problem, we here propose a novel multi-view latent-attention and dynamic discriminative model that jointly learns view-specific and view-shared sub-structures, where the former captures unique dynamics of each view whilst the latter encodes the interaction between the views. Furthermore, a novel multi-view latent-attention variational autoencoder model is introduced in learning the acquired features, enabling us to learn discriminative features in each view. Experimental results on the standard CRMI13 and our multi-view Parkinson's Disease Mouse Behaviour (PDMB) datasets demonstrate that our proposed model outperforms the other state of the arts technologies, has lower computational cost than the other graphical models and effectively deals with the imbalanced data problem.

MARK4 controls ischaemic heart failure through microtubule detyrosination.

Myocardial infarction is a major cause of premature death in adults. Compromised cardiac function after myocardial infarction leads to chronic heart failure with systemic health complications and a high mortality rate1. Effective therapeutic strategies are needed to improve the recovery of cardiac function after myocardial infarction. More specifically, there is a major unmet need for a new class of drugs that can improve cardiomyocyte contractility, because inotropic therapies that are currently available have been associated with high morbidity and mortality in patients with systolic heart failure2,3 or have shown a very modest reduction of risk of heart failure4. Microtubule detyrosination is emerging as an important mechanism for the regulation of cardiomyocyte contractility5. Here we show that deficiency of microtubule-affinity regulating kinase 4 (MARK4) substantially limits the reduction in the left ventricular ejection fraction after acute myocardial infarction in mice, without affecting infarct size or cardiac remodelling. Mechanistically, we provide evidence that MARK4 regulates cardiomyocyte contractility by promoting phosphorylation of microtubule-associated protein 4 (MAP4), which facilitates the access of vasohibin 2 (VASH2)-a tubulin carboxypeptidase-to microtubules for the detyrosination of α-tubulin. Our results show how the detyrosination of microtubules in cardiomyocytes is finely tuned by MARK4 to regulate cardiac inotropy, and identify MARK4 as a promising therapeutic target for improving cardiac function after myocardial infarction.