A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models

Imaging striatal dopamine release using a nongenetically encoded near infrared fluorescent catecholamine nanosensor.

Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000-1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution

Atomically Thin Resonant Tunnel Diodes built from Synthetic van der Waals Heterostructures

Vertical integration of two-dimensional van der Waals materials is predicted to lead to novel electronic and optical properties not found in the constituent layers. Here, we present the direct synthesis of two unique, atomically thin, multi-junction heterostructures by combining graphene with the monolayer transition-metal dichalocogenides: MoS2, MoSe2, and WSe2.The realization of MoS2-WSe2-Graphene and WSe2-MoSe2-Graphene heterostructures leads toresonant tunneling in an atomically thin stack with spectrally narrow room temperature negative differential resistance characteristics

Preconceptional lipid-based nutrient supplementation in 2 low-resource countries results in distinctly different IGF-1/mTOR placental responses

Background: Preconceptional maternal small-quantity lipid-based nutrient supplementation (SQLNS) improved intrauterine linear growth in low-resource countries as demonstrated by the Women First Preconception Maternal Nutrition Trial (WF). Fetal growth is dependent on nutrient availability and regulated by insulin-like growth factor 1 (IGF-1) through changes in placental transfer capacity, mediated by the mechanistic target of rapamycin (mTOR) pathway.Objectives: Our objective was to evaluate the role of placental mTOR and IGF-1 signaling on fetal growth in women from 2 low-resource countries with high rates of stunting after they received preconceptional SQLNS.Methods: We studied 48 women from preconception through delivery who were from Guatemala and Pakistan and received SQLNS or not, as part of the WF study. Placental samples were obtained at delivery (control, n = 24; SQLNS, n = 24). Placental protein or mRNA expression of eukaryotic translation initiation factor binding protein-1 (4E-BP1), ribosomal protein S6 (rpS6), AMP-activated protein kinase α (AMPKA), IGF-1, insulin-like growth factor receptor (IGF-1R), and pregnancy associated plasma protein (PAPP)-A, and DNA methylation of the IGF1 promoter were determined. Maternal serum IGF-1, insulin-like growth factor binding protein (IGFBP)-3, IGFBP-4, IGFBP-5, PAPP-A, PAPP-A2, and zinc were measured.Results: Mean ± SEM maternal prepregnancy BMI differed between participants in Guatemala (26.5 ± 1.3) and Pakistan (19.8 ± 0.7) (P \u3c 0.001). In Pakistani participants, SQLNS increased the placental rpS6(T37/46):rpS6 ratio (1.5-fold) and decreased the AMPKA(T172):AMPKA ratio. Placental IGF1 mRNA expression was positively correlated with birth length and birth weight z-scores. Placental PAPP-A (30-fold) and maternal serum zinc (1.2-fold) increased with SQLNS. In Guatemalan participants SQLNS did not influence placental mTOR signaling. Placental IGF-1R protein expression was positively associated with birth length and birth weight z-scores. SQLNS increased placental PAPP-A (40-fold) and maternal serum IGFBP-4 (1.6-fold).Conclusions: In Pakistani pregnant women with poor nutritional status, preconceptional SQLNS activated placental mTOR and IGF-1 signaling and was associated with improved fetal growth. In contrast, in Guatemalan women SQLNS did not activate placental nutrient-sensing pathways. In populations experiencing childhood stunting, preconceptional SQLNS improves placental function and fetal growth only in the context of poor maternal nutrition. This trial was registered at clinicaltrials.gov as NCT01883193

Form of Supplemental Selenium in Vitamin-Mineral Premixes Differentially Affects Early Luteal and Gestational Concentrations of Progesterone, and Postpartum Concentrations of Prolactin in Beef Cows

Soils with marginal to deficient levels of selenium (Se) are widespread in the northwest, northeast, and southeast US. Supplementation to the diet of forage-grazing beef cattle with a vitamin-mineral mix containing additional Se is recommended in these geographic regions. We have reported that the form of supplemental Se provided to Angus-cross beef cows can affect circulating levels of progesterone (P4) on day 6 of the estrous cycle, a time when increased P4 is known to promote fertility. The objectives of this study were to (1) confirm and expand upon our initial report that the form of Se provided to cows affects early luteal-phase concentrations of systemic P4, (2) determine the effects of the form of Se on concentrations of P4 during gestation, and (3) determine the effects of the form of Se on concentrations of prolactin (PRL) during lactation. Throughout this study, Angus-cross beef cows had ad libitum access to a vitamin-mineral mix containing 35 ppm of Se in either an inorganic form (ISe) or a 1:1 mix of inorganic and organic forms (MIX). We observed a MIX-induced increase (p = 0.006) in systemic concentrations of P4 on day 7 but not on days 4 or 10 of the estrous cycle, consistent with our earlier report. We observed a MIX-induced increase (p = 0.02) in the systemic concentration of P4 at months 1, 3, 5, and 7 of gestation, and a MIX-induced decrease (p \u3c 0.05) in systemic concentrations of PRL at months 5 and 6 of lactation. In summary, the form of Se provided to cows can be manipulated to affect the early luteal phase and gestational concentrations of P4, and postpartum concentrations of PRL

Functional Profiling of Transcription Factor Genes in Neurospora crassa.

Regulation of gene expression by DNA-binding transcription factors is essential for proper control of growth and development in all organisms. In this study, we annotate and characterize growth and developmental phenotypes for transcription factor genes in the model filamentous fungus Neurospora crassa We identified 312 transcription factor genes, corresponding to 3.2% of the protein coding genes in the genome. The largest class was the fungal-specific Zn2Cys6 (C6) binuclear cluster, with 135 members, followed by the highly conserved C2H2 zinc finger group, with 61 genes. Viable knockout mutants were produced for 273 genes, and complete growth and developmental phenotypic data are available for 242 strains, with 64% possessing at least one defect. The most prominent defect observed was in growth of basal hyphae (43% of mutants analyzed), followed by asexual sporulation (38%), and the various stages of sexual development (19%). Two growth or developmental defects were observed for 21% of the mutants, while 8% were defective in all three major phenotypes tested. Analysis of available mRNA expression data for a time course of sexual development revealed mutants with sexual phenotypes that correlate with transcription factor transcript abundance in wild type. Inspection of this data also implicated cryptic roles in sexual development for several cotranscribed transcription factor genes that do not produce a phenotype when mutated

Enzyme-Responsive Snap-Top Covered Silica Nanocontainers

Mesoporous silica nanoparticles, capable of storing a payload of small molecules and releasing it following specific catalytic activation by an esterase, have been designed and fabricated. The storage and release of the payload is controlled by the presence of [2]rotaxanes, which consist of tri(ethylene glycol) chains threaded by α-cyclodextrin tori, located on the surfaces of the nanoparticles and terminated by a large stoppering group. These modified silica nanoparticles are capable of encapsulating guest molecules when the [2]rotaxanes are present. The bulky stoppers, which serve to hold the tori in place, are stable under physiological conditions but are cleaved by the catalytic action of an enzyme, causing dethreading of the tori and release of the guest molecules from the pores of the nanoparticles. These snap-top covered silica nanocontainers (SCSNs) are prepared by a modular synthetic method, in which the stoppering unit, incorporated in the final step of the synthesis, may be changed at will to target the response of the system to any of a number of hydrolytic enzymes. Here, the design, synthesis, and operation of model SCSNs that open in the presence of porcine liver esterase (PLE) are reported. The empty pores of the silica nanoparticles were loaded with luminescent dye molecules (rhodamine B), and stoppering units that incorporate adamantyl ester moieties were then attached in the presence of α-cyclodextrin using the copper-catalyzed azide−alkyne cycloaddition (CuAAC), closing the SCSNs. The release of rhodamine-B from the pores of the SCSN, following PLE-mediated hydrolysis of the stoppers, was monitored using fluorescence spectroscopy

The origins of unpredictability in life trajectory prediction tasks

Why are life trajectories difficult to predict? We investigated this question through in-depth qualitative interviews with 40 families sampled from a multi-decade longitudinal study. Our sampling and interviewing process were informed by the earlier efforts of hundreds of researchers to predict life outcomes for participants in this study. The qualitative evidence we uncovered in these interviews combined with a well-known mathematical decomposition of prediction error helps us identify some origins of unpredictability and create a new conceptual framework. Our specific evidence and our more general framework suggest that unpredictability should be expected in many life trajectory prediction tasks, even in the presence of complex algorithms and large datasets. Our work also provides a foundation for future empirical and theoretical work on unpredictability in human lives.Comment: 54 pages, 8 figure