Astronauts who spend significant time in space may experience intracranial hypertension (pressure inside the skull), which often does not normalize upon return to Earth. This type of intracranial pressure can cause vision problems, headaches, glaucoma, and other serious health problems, making it a significant obstacle to long-duration space exploration missions. NASA is hoping that a better understanding of how central nervous system stem cells divide in microgravity will help lead to ways to protect astronauts from problems with intracranial pressure and to design adequate preventive measures. These studies examine cell growth and division of neural stem cells that experienced microgravity on the International Space Station and were returned to normal gravity prior to live-cell imaging studies to determine cell changes.

Remarkable discoveries such as condensed chromatin in duckbill dinosaur cartilage and newly presented discoveries of dinosaur vascular veins, venule valves, and nerve fibers (this report) warrant study of global dinosaur remains for preserved soft tissue (dST). Dinosaur osteocytes feature dendritic projections (filipodia) of lengths up to 18 µm, while osteocytes collected from a Triceratops horn have lengths of 25 µm or longer. While preservation methods for dST involve the degradation of sugars into glycation end products and the employment of highly oxidative hydroxyl radicals to “fix” tissues, we note that lengthy and narrow osteocyte filipodia show no signs of hydroxyl radical infiltration into the lacuna-canalicular network. Moreover, our ultraviolet fluorescence (UVFL) study of Triceratops horn, rib, vertebra, and frill thin sections shows extensive clotting in most vessel canals, probably as a result of asphyxia while drowning. Further UVFL autofluorescence study of dinosaur bone sections is vital for characterization of dinosaur blood clots.

Monte Carlo simulations are commonly used in elemental quantification using energy-dispersive spectroscopy (EDS). Here, the Monte Carlo program MC X-ray was incorporated into the image processing software Dragonfly by Object Research Systems (ORS) as a simulation library. The simulation program has been transformed into a complete microscope simulator where the tools of Dragonfly allow complex voxel-based geometries to be constructed, and the electron beam and detectors can be freely placed inside the 3D space. Computation times of simulations have been improved drastically through new data structures and parallelization. Simulations of backscattered electron imaging and EDS mapping are presented here to demonstrate the capabilities of this new library.

In the 50 years since the first mating of semiconductor-based energy-dispersive X-ray spectrometry (EDS) with the scanning electron microscope (SEM), this hybrid instrument has become an indispensable microanalytical tool. In the last two decades a new detector, the silicon drift detector (SDD), has overtaken earlier Si(Li) technology and has made EDS in the SEM and TEM faster and better. This article tells the story of the SDD development and describes improvements in count rate capability, energy resolution, and detector geometry that bring to SEM microanalysis exceptional precision and stability. Quality maps of element distributions can now be obtained in minutes instead of hours.

While conventional negative stain electron microscopy (NSEM) has been used extensively for imaging and characterizing high density lipoprotein (HDL) particles, traditional methods have not provided high-level particle surface detail. To obtain greater detail of HDL particles, we developed a modified negative staining procedure using a uranyl formate staining solution that maintains particle morphology and provides improved surface detail. The additional surface detail has allowed us to perform single-particle analysis on whole HDL particle preparations. It has also allowed us to explore interactions between HDL particle surface proteins such as Apo A with proteins that interact with Apo A such as lecithin-cholesterol acyltransferase (LCAT).