Line-Scanning Particle Image Velocimetry: An Optical Approach for Quantifying a Wide Range of Blood Flow Speeds in Live Animals

The ability to measure blood velocities is critical for studying vascular development, physiology, and pathology. A key challenge is to quantify a wide range of blood velocities in vessels deep within living specimens with concurrent diffraction-limited resolution imaging of vascular cells. Two-photon laser scanning microscopy (TPLSM) has shown tremendous promise in analyzing blood velocities hundreds of micrometers deep in animals with cellular resolution. However, current analysis of TPLSM-based data is limited to the lower range of blood velocities and is not adequate to study faster velocities in many normal or disease conditions.We developed line-scanning particle image velocimetry (LS-PIV), which used TPLSM data to quantify peak blood velocities up to 84 mm/s in live mice harboring brain arteriovenous malformation, a disease characterized by high flow. With this method, we were able to accurately detect the elevated blood velocities and exaggerated pulsatility along the abnormal vascular network in these animals. LS-PIV robustly analyzed noisy data from vessels as deep as 850 µm below the brain surface. In addition to analyzing in vivo data, we validated the accuracy of LS-PIV up to 800 mm/s using simulations with known velocity and noise parameters.To our knowledge, these blood velocity measurements are the fastest recorded with TPLSM. Partnered with transgenic mice carrying cell-specific fluorescent reporters, LS-PIV will also enable the direct in vivo correlation of cellular, biochemical, and hemodynamic parameters in high flow vascular development and diseases such as atherogenesis, arteriogenesis, and vascular anomalies

Biogenic gas nanostructures as ultrasonic molecular reporters

Ultrasound is among the most widely used non-invasive imaging modalities in biomedicine, but plays a surprisingly small role in molecular imaging due to a lack of suitable molecular reporters on the nanoscale. Here, we introduce a new class of reporters for ultrasound based on genetically encoded gas nanostructures from microorganisms, including bacteria and archaea. Gas vesicles are gas-filled protein-shelled compartments with typical widths of 45–250 nm and lengths of 100–600 nm that exclude water and are permeable to gas. We show that gas vesicles produce stable ultrasound contrast that is readily detected in vitro and in vivo, that their genetically encoded physical properties enable multiple modes of imaging, and that contrast enhancement through aggregation permits their use as molecular biosensors

Environmental effects of ozone depletion, UV radiation and interactions with climate change : UNEP Environmental Effects Assessment Panel, update 2017

Peer reviewe

Predicting Milk Yield of Holstein Cows from 306 to 395 Days in Milk

Prediction equations were determined to estimate daily milk yield from 306 to 395 d in milk for forecasting herd milk sales from Holstein cows in lactation \u3e 305 d. Data were test day milk weights for 65,322 primiparous and 119,220 pluriparous lactations of \u3e 305 d from the Southern US. A forecast model was developed using same lactation 305 d milk yield (in classes of 500 kg increments) that gave similar predicted daily yields as models utilizing last sample milk weight information. This model has the advantage of early forecasting of later milk using projected 305-d yields. Reduced forecast models ignoring days pregnant, yield class, or both accounted for 95, 68, and 59%, and 91, 67, and 56% as much variation in daily milk as the full model for the primiparous and pluriparous cows. Percentage of 305-d milk yielded in mo 11, 12, and 13, depending on 305-d yield class, ranged from 7.1 to 7.0%, 6.2 to 6.0%, and 5.4 to 5.0%, and 5.4 to 5.0%, 4.3 to 3.9%, and 3.3 to 3.0% for first parity and pluriparous cows calving in winter and 125 d open. Cows not calving in winter or with more than 125 d open yielded more milk in extended lactation. These percentages are larger than generally assumed in studies of days open, thus indicating that cost of days open may have been overestimated