Strain-controlled criticality governs the nonlinear mechanics of fibre networks

Disordered fibrous networks are ubiquitous in nature as major structural components of living cells and tissues. The mechanical stability of networks generally depends on the degree of connectivity: only when the average number of connections between nodes exceeds the isostatic threshold are networks stable (Maxwell, J. C., Philosophical Magazine 27, 294 (1864)). Upon increasing the connectivity through this point, such networks undergo a mechanical phase transition from a floppy to a rigid phase. However, even sub-isostatic networks become rigid when subjected to sufficiently large deformations. To study this strain-controlled transition, we perform a combination of computational modeling of fibre networks and experiments on networks of type I collagen fibers, which are crucial for the integrity of biological tissues. We show theoretically that the development of rigidity is characterized by a strain-controlled continuous phase transition with signatures of criticality. Our experiments demonstrate mechanical properties consistent with our model, including the predicted critical exponents. We show that the nonlinear mechanics of collagen networks can be quantitatively captured by the predictions of scaling theory for the strain-controlled critical behavior over a wide range of network concentrations and strains up to failure of the material

Particle tracking for polydisperse sedimenting droplets in phase separation

When a binary fluid demixes under a slow temperature ramp, nucleation, coarsening and sedimentation of droplets lead to an oscillatory evolution of the phase separating system. The advection of the sedimenting droplets is found to be chaotic. The flow is driven by density differences between the two phases. Here, we show how image processing can be combined with particle tracking to resolve droplet size and velocity simultaneously. Droplets are used as tracer particles, and the sedimentation velocity is determined. Taking these effects into account, droplets with radii in the range of 4 -- 40 micrometers are detected and tracked. Based on this data we resolve the oscillations in the droplet size distribution which are coupled to the convective flow.Comment: 13 pages; 16 figures including 3 photographs and 3 false-color plot

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data

We introduce a wide and deep neural network for prediction of progression from patients with mild cognitive impairment to Alzheimer's disease. Information from anatomical shape and tabular clinical data (demographics, biomarkers) are fused in a single neural network. The network is invariant to shape transformations and avoids the need to identify point correspondences between shapes. To account for right censored time-to-event data, i.e., when it is only known that a patient did not develop Alzheimer's disease up to a particular time point, we employ a loss commonly used in survival analysis. Our network is trained end-to-end to combine information from a patient's hippocampus shape and clinical biomarkers. Our experiments on data from the Alzheimer's Disease Neuroimaging Initiative demonstrate that our proposed model is able to learn a shape descriptor that augments clinical biomarkers and outperforms a deep neural network on shape alone and a linear model on common clinical biomarkers.Comment: Data and Machine Learning Advances with Multiple Views Workshop, ECML-PKDD 201

Symptomatic cardiac metastases of breast cancer 27 years after mastectomy: a case report with literature review - pathophysiology of molecular mechanisms and metastatic pathways, clinical aspects, diagnostic procedures and treatment modalities.

Metastases to the heart and pericardium are rare but more common than primary cardiac tumours and are generally associated with a rather poor prognosis. Most cases are clinically silent and are undiagnosed in vivo until the autopsy. We present a female patient with a 27-year-old history of an operated primary breast cancer who was presented with dyspnoea, paroxysmal nocturnal dyspnoea and orthopnoea. The clinical signs and symptoms aroused suspicion of congestive heart failure. However, the cardiac metastases were detected during a routine cardiologic evaluation and confirmed with computed tomography imaging. Additionally, this paper outlines the pathophysiology of molecular and clinical mechanisms involved in the metastatic spreading, clinical presentation, diagnostic procedures and treatment of heart metastases. The present case demonstrates that a complete surgical resection and systemic chemotherapy may result in a favourable outcome for many years. However, a lifelong medical follow-up, with the purpose of a detection of metastases, is highly recommended. We strongly call the attention of clinicians to the fact that during the follow-up of all cancer patients, such heart failure may be a harbinger of the secondary heart involvement