Awake chronic mouse model of targeted pial vessel occlusion via photothrombosis

Animal models of stroke are used extensively to study the mechanisms involved in the acute and chronic phases of recovery following stroke. A translatable animal model that closely mimics the mechanisms of a human stroke is essential in understanding recovery processes as well as developing therapies that improve functional outcomes. We describe a photothrombosis stroke model that is capable of targeting a single distal pial branch of the middle cerebral artery with minimal damage to the surrounding parenchyma in awake head-fixed mice. Mice are implanted with chronic cranial windows above one hemisphere of the brain that allow optical access to study recovery mechanisms for over a month following occlusion. Additionally, we study the effect of laser spot size used for occlusion and demonstrate that a spot size with small axial and lateral resolution has the advantage of minimizing unwanted photodamage while still monitoring macroscopic changes to cerebral blood flow during photothrombosis. We show that temporally guiding illumination using real-time feedback of blood flow dynamics also minimized unwanted photodamage to the vascular network. Finally, through quantifiable behavior deficits and chronic imaging we show that this model can be used to study recovery mechanisms or the effects of therapeutics longitudinally.R01 EB021018 - NIBIB NIH HHS; R01 MH111359 - NIMH NIH HHS; R01 NS108472 - NINDS NIH HHSPublished versio

Anatomy of STEM Teaching in American Universities: A Snapshot from a Large-Scale Observation Study

National and local initiatives focused on the transformation of STEM teaching in higher education have multiplied over the last decade. These initiatives often focus on measuring change in instructional practices, but it is difficult to monitor such change without a national picture of STEM educational practices, especially as characterized by common observational instruments. We characterized a snapshot of this landscape by conducting the first large scale observation-based study. We found that lecturing was prominent throughout the undergraduate STEM curriculum, even in classrooms with infrastructure designed to support active learning, indicating that further work is required to reform STEM education. Additionally, we established that STEM faculty’s instructional practices can vary substantially within a course, invalidating the commonly-used teaching evaluations based on a one-time observation

Multi-scale laser speckle contrast imaging of microcirculatory vasoreactivity

Laser speckle contrast imaging is a robust and versatile blood flow imaging tool in basic and clinical research for its relatively simple construction and ease of customization. One of its key features is the scalability of the imaged field of view. With minimal changes to the system or analysis, laser speckle contrast imaging allows for high-resolution blood flow imaging through cranial windows or low-resolution perfusion visualization of perfusion over large areas, e.g. in human skin. We further utilize this feature and introduce a multi-scale laser speckle contrast imaging system, which we apply to study vasoreactivity in renal microcirculation. We combine high resolution (small field of view) to segment blood flow in individual vessels with low resolution (large field of view) to monitor global blood flow changes across the renal surface. Furthermore, we compare their performance when analyzing blood flow dynamics potentially associated with a single nephron and show that the previously published approaches, based on low-zoom imaging alone, provide inaccurate results in such applications

Major depressive disorder during pregnancy: Psychiatric medications have minimal effects on the fetus and infant yet development is compromised

Psychotropic medication use and psychiatric symptoms during pregnancy each are associated with adverse neurodevelopmental outcomes in offspring. Commonly, studies considering medication effects do not adequately assess symptoms, nor evaluate children when the effects are believed to occur, the fetal period. This study examined maternal serotonin reuptake inhibitor and polypharmacy use in relation to serial assessments of five indices of fetal neurobehavior and Bayley Scales of Infant Development at 12 months in N = 161 socioeconomically advantaged, non-Hispanic White women with a shared risk phenotype, diagnosed major depressive disorder. On average fetuses showed the expected development over gestation. In contrast, infant average Bayley psychomotor and mental development scores were low (M = 84.10 and M = 89.92, range of normal limits 85–114) with rates of delay more than 2–3 times what would be expected based on this measure's normative data. Controlling for prenatal and postnatal depressive symptoms, prenatal medication effects on neurobehavioral development were largely undetected in the fetus and infant. Mental health care directed primarily at symptoms may not address the additional psychosocial needs of women parenting infants. Speculatively, prenatal serotonin reuptake inhibitor exposure may act as a plasticity rather than risk factor, potentially enhancing receptivity to a nonoptimal postnatal environment in some mother–infant dyads

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702 μm. Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before

Oil palm genome sequence reveals divergence of interfertile species in Old and New worlds

Oil palm is the most productive oil-bearing crop. Although it is planted on only 5% of the total world vegetable oil acreage, palm oil accounts for 33% of vegetable oil and 45% of edible oil worldwide, but increased cultivation competes with dwindling rainforest reserves. We report the 1.8-gigabase (Gb) genome sequence of the African oil palm Elaeis guineensis, the predominant source of worldwide oil production. A total of 1.535 Gb of assembled sequence and transcriptome data from 30 tissue types were used to predict at least 34,802 genes, including oil biosynthesis genes and homologues of WRINKLED1 (WRI1), and other transcriptional regulators, which are highly expressed in the kernel. We also report the draft sequence of the South American oil palm Elaeis oleifera, which has the same number of chromosomes (2n = 32) and produces fertile interspecific hybrids with E. guineensis but seems to have diverged in the New World. Segmental duplications of chromosome arms define the palaeotetraploid origin of palm trees. The oil palm sequence enables the discovery of genes for important traits as well as somaclonal epigenetic alterations that restrict the use of clones in commercial plantings, and should therefore help to achieve sustainability for biofuels and edible oils, reducing the rainforest footprint of this tropical plantation crop