Prevalence of avian hematozoa in central Vermont

Peripheral blood smears from 1,547 birds, of 50 species, from 15 families trapped in Northfield, Vermont were examined for hematozoa. Numerous new host-parasite relationships were identified. The prevalence of all species of parasites over the 3 yr of the study was 42.5%. Prevalence of the genera of parasites were: Leucocytozoon--36.5%; Trypanosoma--7.3%; Haemoproteus--6.3%; microfilariae--1.0%; Plasmodium--1.0%. Peak prevalence (78.9%) occurred in the first half of July. Peak intensity was seen in the last half of June. Evidence from immature birds suggested that active transmission of all genera of hematozoans took place in the study area. Leucocytozoon gametocytes, unlike Haemoproteus gametocytes, were detected in smears from birds during all seasons of the year, and showed no period of complete remission. Trypanosoma and microfilariae also were seen throughout the year.     

Schistosoma mansoni: factors affecting hatching of eggs

The effect of light, oxygen tension, reducing conditions and thermal shock on egg hatching in Schistosoma mansoni were examined. Hatching was found to be unaffected by light or dark conditions or aerobic or anaerobic conditions. Cold shock from 15 to 120 sec was also ineffective in stimulating hatching. The reducing agents ascorbic acid and cysteine inhibited egg hatching. However, the oxidized forms of these compounds inhibited hatching as well, indicating that the reducing conditions they provided were not responsible for the inhibition.     

The unbiased estimation of the fraction of variance explained by a model

The correlation coefficient squared, r², is commonly used to validate quantitative models on neural data, yet it is biased by trial-to-trial variability: as trial-to-trial variability increases, measured correlation to a model’s predictions decreases. As a result, models that perfectly explain neural tuning can appear to perform poorly. Many solutions to this problem have been proposed, but no consensus has been reached on which is the least biased estimator. Some currently used methods substantially overestimate model fit, and the utility of even the best performing methods is limited by the lack of confidence intervals and asymptotic analysis. We provide a new estimator, r^ER2, that outperforms all prior estimators in our testing, and we provide confidence intervals and asymptotic guarantees. We apply our estimator to a variety of neural data to validate its utility. We find that neural noise is often so great that confidence intervals of the estimator cover the entire possible range of values ([0, 1]), preventing meaningful evaluation of the quality of a model’s predictions. This leads us to propose the use of the signal-to-noise ratio (SNR) as a quality metric for making quantitative comparisons across neural recordings. Analyzing a variety of neural data sets, we find that up to ∼ 40% of some state-of-the-art neural recordings do not pass even a liberal SNR criterion. Moving toward more reliable estimates of correlation, and quantitatively comparing quality across recording modalities and data sets, will be critical to accelerating progress in modeling biological phenomena.     

Characterizing the decay of ancient Chinese silk fabrics by microbeam synchrotron radiation diffraction

Scanning synchrotron radiation microdiffraction with an approximately 1 x 1 microm(2) beam has been used as a novel method for characterizing the decay of several T'ang dynasty (618-907 AD) silk fabrics. The crystalline fraction could be visualized based on beta-sheet 210 reflection intensities, extracted by recursive peak fits from several thousand diffraction patterns recorded during mesh scans. The azimuthal width of the 210 reflection, which is related to the orientation distribution of the crystalline domains within nanofibrils and the macroscopic orientation of the fibers traversed by the beam, was found to be sensitive to the overall state of decay of the fabric. The fine structure of the histogram of azimuthal width was related to the fiber hierarchical microstructure and the fabric morphology. SAXS/WAXS analysis supports the assumption of an initial loss of the random chain network with decay. At a subsequent state of aging, decay proceeds into the nanofibrils and the silk fibers break up into even smaller fractions.     

A novel cellular protein, VPEF, facilitates vaccinia virus penetration into HeLa cells through fluid phase endocytosis

Vaccinia virus is a large DNA virus that infects many cell cultures in vitro and animal species in vivo. Although it has been used widely as a vaccine, its cell entry pathway remains unclear. In this study, we showed that vaccinia virus intracellular mature virions bound to the filopodia of HeLa cells and moved toward the cell body and entered the cell through an endocytic route that required a dynamin-mediated pathway but not a clathrin- or caveola-mediated pathway. Moreover, virus penetration required a novel cellular protein, vaccinia virus penetration factor (VPEF). VPEF was detected on cell surface lipid rafts and on vesicle-like structures in the cytoplasm. Both vaccinia virus and dextran transiently colocalized with VPEF, and, importantly, knockdown of VPEF expression blocked vaccinia virus penetration as well as intracellular transport of dextran, suggesting that VPEF mediates vaccinia virus entry through a fluid uptake endocytosis process in HeLa cells. Intracellular VPEF-containing vesicles did not colocalize with Rab5a or caveolin but partially colocalized with Rab11, supporting the idea that VPEF plays a role in vesicle trafficking and recycling in HeLa cells. In summary, this study characterized the mechanism by which vaccinia virus enters HeLa cells and identified a cellular factor, VPEF, that is exploited by vaccinia virus for cell entry through fluid phase endocytosis.     

Identification of 2,3-dihydro-1H-pyrrolo[3,4-c]pyridine-derived ureas as potent inhibitors of human nicotinamide phosphoribosyltransferase (NAMPT)

Potent nicotinamide phosphoribosyltransferase (NAMPT) inhibitors containing 2,3-dihydro-1H-pyrrolo[3,4-c]pyridine-derived ureas were identified using structure-based design techniques. The new compounds displayed improved aqueous solubilities, determined using a high-throughput solubility assessment, relative to previously disclosed urea and amide-containing NAMPT inhibitors. An optimized 2,3-dihydro-1H-pyrrolo[3,4-c]pyridine-derived compound exhibited potent anti-NAMPT activity (18; BC NAMPT IC₅₀ = 11 nM; PC-3 antiproliferative IC₅₀ = 36 nM), satisfactory mouse PK properties, and was efficacious in a PC-3 mouse xenograft model. The crystal structure of another optimized compound (29; NAMPT IC₅₀ = 10 nM; A2780 antiproliferative IC₅₀ = 7 nM) in complex with the NAMPT protein was also determined.     

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.