Deciphering single- and multi-particle trapping dynamics under femtosecond pulsed excitation with simultaneous spatial and temporal resolution

Recent theoretical and experimental studies have shed light on how optical trapping dynamics under femtosecond pulsed excitation are fine-tuned by optical and thermal nonlinearities. Here, we present experimental results of nonlinear optical trapping of single and multiple polystyrene beads (of 1 μm diameter). We show how integration and synchronization of bright-filed video microscopy with confocal detection of backscatter provide both spatial and temporal resolution required to capture intricate details of trapping dynamics. Such spatiotemporal detection is promising to have far-reaching applications in exploring controlled optical trapping and manipulations harnessed by optical and thermal nonlinearities.

Multispectral intravital microscopy for simultaneous bright-field and fluorescence imaging of the microvasculature

Intravital video microscopy permits the observation of microcirculatory blood flow. This often requires fluorescent probes to visualize structures and dynamic processes that cannot be observed with conventional bright-field microscopy. Conventional light microscopes do not allow for simultaneous bright-field and fluorescent imaging. Moreover, in conventional microscopes, only one type of fluorescent label can be observed. This study introduces multispectral intravital video microscopy, which combines bright-field and fluorescence microscopy in a standard light microscope. The technique enables simultaneous real-time observation of fluorescently-labeled structures in relation to their direct physical surroundings. The advancement provides context for the orientation, movement, and function of labeled structures in the microcirculation.

Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy

Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging process, evaluating experiments very time consuming and susceptible to human error. Since more advanced digital cameras are used in IVM, the experimental data volume will also increase significantly. This study presents a new two-step image processing algorithm that uses a trained Convolutional Neural Network (CNN) to functionally analyze IVM microscopic images without the need for manual analysis. While the first step uses a modified vessel segmentation algorithm to extract the location of vessel-like structures, the second step uses a 3D-CNN to assess whether the vessel-like structures have blood flowing in it or not. We demonstrate that our two-step algorithm can efficiently analyze IVM image data with high accuracy (83%). To our knowledge, this is the first application of machine learning for the functional analysis of microvascular blood flow in vivo.

Laboratory experiments on secondary ice production upon free falling drizzle droplets observed by high speed video and thermal imaging

<p>During the freezing of supercooled drizzle droplets, the ice shell forms at the droplet surface and propagates inwards, causing a pressure rise in the droplet core. If the pressure exceeds the mechanical stability of the ice shell, the shell can crack open and eject secondary ice particles or cause the full disintegration of the ice shell leading to droplet shattering. Recent in-cloud observations and modeling studies have suggested the importance of secondary ice production upon shattering of freezing drizzle droplets. The details of this process are poorly understood and the number of secondary ice particles produced during freezing remains to be quantified.</p><p>Here we present insight into experiments with freezing drizzle droplets levitated in electrodynamic balance under controlled conditions with respect to temperature, humidity and airflow velocity. Individual droplets are exposed to a flow of cold air from below, simulating free fall conditions. The freezing process is observed with high-speed video microscopy and a high-resolution infrared thermal measuring system. We show the observed frequencies for various events associated with the production of secondary ice particles during freezing for pure water droplets and aqueous solution of analogue sea salt droplets (300 µm in diameter) and report a strong enhancement of the shattering probability as compared to our previous study (Lauber et al., 2018) conducted in stagnant air. Analysis of pressure release events recorded by high-resolution infrared thermography suggest that pressure release events associated with the possible ejection of secondary ice particles occur far more frequent than previously quantified with observations by high speed video microscopy only.</p><p> </p><p>Lauber, A., A. Kiselev, T. Pander, P. Handmann, and T Leisner (2018). “Secondary Ice Formation during Freezing of Levitated Droplets”, Journal of the Atmospheric Sciences 75, pp. 2815–2826. </p>