Search for: All records

Rotational and vibrational energy relaxation (RER and VER) of N2O embedded in xenon and SF6 environments ranging from the gas phase to the liquid, including the supercritical regime, is studied at a molecular level. Calibrated intermolecular interactions from high-level electronic structure calculations, validated against experiments for the pure solvents, were used to carry out classical molecular dynamics simulations corresponding to experimental state points for near-critical isotherms. The computed RER rates in low-density solvents of krotXe=(3.67±0.25)×1010 s−1 M−1 and krotSF6=(1.25±0.12)×1011 s−1 M−1 compare well with the rates determined by the analysis of two-dimensional infrared experiments. Simulations find that an isolated binary collision description is successful up to solvent concentrations of ∼4 M. For higher densities, including the supercritical regime, the simulations do not correctly describe RER, probably due to the neglect of solvent–solute coupling in the analysis of the rotational motion. For VER, the near-quantitative agreement between simulations and pump–probe experiments captures the solvent density-dependent trends. 

Prostate cancer prognostication largely relies on visual assessment of a few thinly sectioned biopsy specimens under a microscope to assign a Gleason grade group (GG). Unfortunately, the assigned GG is not always associated with a patient’s outcome in part because of the limited sampling of spatially heterogeneous tumors achieved by 2-dimensional histopathology. In this study, open-top light-sheet microscopy was used to obtain 3-dimensional pathology data sets that were assessed by 4 human readers. Intrabiopsy variability was assessed by asking readers to perform Gleason grading of 5 different levels per biopsy for a total of 20 core needle biopsies (ie, 100 total images). Intrabiopsy variability (Cohen k) was calculated as the worst pairwise agreement in GG between individual levels within each biopsy and found to be 0.34, 0.34, 0.38, and 0.43 for the 4 pathologists. These preliminary results reveal that even within a 1-mm-diameter needle core, GG based on 2-dimensional images can vary dramatically depending on the location within a biopsy being analyzed. We believe that morphologic assessment of whole biopsies in 3 dimension has the potential to enable more reliable and consistent tumor grading. 

The density dependence of rotational and vibrational energy relaxation (RER and VER) of the N 2 O ν 3 asymmetric stretch in dense gas and supercritical Xe and SF 6 solutions for near critical isotherms is measured by ultrafast 2DIR and infrared pump–probe spectroscopy. 2DIR analysis provides precise measurements of RER at all gas and supercritical solvent densities. An isolated binary collision (IBC) model is sufficient to describe RER for solvent densities ≤ ∼4M where rotational equilibrium is re-established in ∼1.5–2.5 collisions. N 2 O RER is ∼30% more efficient in SF 6 than in Xe due to additional relaxation pathways in SF 6 and electronic factor differences. 2DIR analysis revealed that N 2 O RER exhibits a critical slowing effect in SF 6 at near critical density ( ρ* ∼ 0.8) where the IBC model breaks down. This is attributable to the coupling of critical long-range density fluctuations to the local N 2 O free rotor environment. No such RER critical slowing is observed in Xe because IBC break down occurs much further from the Xe critical point. Many body interactions effectively shield N 2 O from these near critical Xe density fluctuations. The N 2 O ν 3 VER density dependence in SF 6 is different than that seen for RER, indicating a different coupling to the near critical environment than RER. N 2 O ν 3 VER is only about ∼7 times slower than RER in SF 6 . In contrast, almost no VER decay is observed in Xe over 200 ps. This VER solvent difference is due to a vibrationally resonant energy transfer pathway in SF 6 that is not possible for Xe. 

Epibionts are organisms that utilize the exterior of other organisms as a living substratum. Many affiliate opportunistically with hosts of different species, but others specialize on particular hosts as obligate associates. We investigated a case of apparent host specificity between two barnacles that are epizoites of sea turtles and illuminate some ecological considerations that may shape their host relationships. The barnaclesChelonibia testudinariaandChelonibia caretta, though roughly similar in appearance, are separable by distinctions in morphology, genotype, and lifestyle. However, though each is known to colonize both green (Chelonia mydas) and hawksbill (Eretmochelys imbricata) sea turtles,C. testudinariais >5 times more common on greens, whileC. carettais >300 times more common on hawksbills. Two competing explanations for this asymmetry in barnacle incidence are either that the species’ larvae are spatially segregated in mutually exclusive host-encounter zones or their distributions overlap and the larvae behaviorally select their hosts from a common pool. We indirectly tested the latter by documenting the occurrence of adults of both barnacle species in two locations (SE Florida and Nose Be, Madagascar) where both turtle species co-mingle. For green and hawksbill turtles in both locations (Florida:n= 32 andn= 275, respectively; Madagascar:n= 32 andn= 125, respectively), we found thatC. testudinariaoccurred on green turtles only (percent occurrence – FL: 38.1%; MD: 6.3%), whereas the barnacleC. carettawas exclusively found on hawksbill turtles (FL: 82.2%; MD: 27.5%). These results support the hypothesis that the larvae of these barnacles differentially select host species from a shared supply. Physio-biochemical differences in host shell material, conspecific chemical cues, external microbial biofilms, and other surface signals may be salient factors in larval selectivity. Alternatively, barnacle presence may vary by host micro-environment. Dissimilarities in scute structure and shell growth between hawksbill and green turtles may promote critical differences in attachment modes observed between these barnacles. In understanding the co-evolution of barnacles and hosts it is key to consider the ecologies of both hosts and epibionts in interpreting associations of chance, choice, and dependence. Further studies are necessary to investigate the population status and settlement spectrum of barnacles inhabiting sea turtles. 

For the last two decades, high-dimensional data and methods have proliferated throughout the literature. Yet, the classical technique of linear regression has not lost its usefulness in applications. In fact, many high-dimensional estimation techniques can be seen as variable selection that leads to a smaller set of variables (a “submodel”) where classical linear regression applies. We analyze linear regression estimators resulting from model selection by proving estimation error and linear representation bounds uniformly over sets of submodels. Based on deterministic inequalities, our results provide “good” rates when applied to both independent and dependent data. These results are useful in meaningfully interpreting the linear regression estimator obtained after exploring and reducing the variables and also in justifying post-model-selection inference. All results are derived under no model assumptions and are nonasymptotic in nature.