A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching

Analysts often estimate treatment effects in observational studies using propensity score matching techniques. When there are missing covariate values, analysts can multiply impute the missing data to create m completed data sets. Analysts can then estimate propensity scores on each of the completed data sets, and use these to estimate treatment effects. However, there has been relatively little attention on developing imputation models to deal with the additional problem of missing treatment indicators, perhaps due to the consequences of generating implausible imputations. However, simply ignoring the missing treatment values, akin to a complete case analysis, could also lead to problems when estimating treatment effects. We propose a latent class model to multiply impute missing treatment indicators. We illustrate its performance through simulations and with data taken from a study on determinants of children's cognitive development. This approach is seen to obtain treatment effect estimates closer to the true treatment effect than when employing conventional imputation procedures as well as compared to a complete case analysis.     

Odontocete spatial patterns and temporal drivers of detection at sites in the Hawaiian islands

Successful conservation and management of marine top predators rely on detailed documentation of spatiotemporal behavior. For cetacean species, this information is key to defining stocks, habitat use, and mitigating harmful interactions. Research focused on this goal is employing methodologies such as visual observations, tag data, and passive acoustic monitoring (PAM) data. However, many studies are temporally limited or focus on only one or few species. In this study, we make use of an existing long-term (2009–2019), labeled PAM data set to examine spatiotemporal patterning of at least 10 odontocete (toothed whale) species in the Hawaiian Islands using compositional analyses and modeling techniques. Species composition differs among considered sites, and this difference is robust to seasonal movement patterns. Temporally, hour of day was the most significant predictor of detection across species and sites, followed by season, though patterns differed among species. We describe long-term trends in species detection at one site and note that they are markedly similar for many species. These trends may be related to long-term, underlying oceanographic cycles that will be the focus of future study. We demonstrate the variability of temporal patterns even at relatively close sites, which may imply that wide-ranging models of species presence are missing key fine-scale movement patterns. Documented seasonal differences in detection also highlights the importance of considering season in survey design both regionally and elsewhere. We emphasize the utility of long-term, continuous monitoring in highlighting temporal patterns that may relate to underlying climatic states and help us predict responses to climate change. We conclude that long-term PAM records are a valuable resource for documenting spatiotemporal patterns and can contribute many insights into the lives of top predators, even in highly studied regions such as the Hawaiian Islands.     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

North Sea cod and climate change – modelling the effects of temperature on population dynamics

In order to examine the likely impacts of climate change on fish stocks, it is necessary to couple the output from large‐scale climate models to fisheries population simulations. Using projections of future North Sea surface temperatures for the period 2000–2050 from the Hadley General Circulation Model, we estimate the likely effects of climate change on the North Sea cod population. Output from the model suggests that increasing temperatures will lead to an increased rate of decline in the North Sea cod population compared with simulations that ignore environmental change. Although the simulation developed here is relatively simplistic, we demonstrate that inclusion of environmental factors in population models can markedly alter one's perception of how the population will behave. The development of simulations incorporating environment effects will become increasingly important as the impacts of climate change on the marine ecosystem become more pronounced.     

Birthweight discordance in multiple pregnancy.

This paper reviews several aspects of discordant growth in multiple pregnancies. Discordant growth is not a chance event and therefore several patterns can be discerned. About 75% of twins exhibit < 15% discordance (concordant), 20% are 15-25% (mildly) discordant, and about 5% are more than 25% (severely) discordant. Higher frequencies and increased severity are seen among triplets. Five observations regarding discordance became generally accepted: (a) not all discordant pairs are similar; (b) the larger the discordance level the greater is the risk for an adverse outcome; (c) discordant growth does not necessarily represent growth restriction; (d) a discordance level may have a different clinical implication in different gestational ages; and (e) the smaller fetuses in severely discordant pairs are at disproportionate risk for neonatal mortality. Mild discordance may represent a normal variation between sibs whereas severely discordant pairs often exhibit patterns of growth restriction. Not infrequently, discordance may represent an adaptation to the limited intrauterine space in order to increase gestational age.     

Energy cost of walking and gait instability in healthy 65- and 80-yr-olds.

This study tested whether the lower economy of walking in healthy elderly subjects is due to greater gait instability. We compared the energy cost of walking and gait instability (assessed by stride to stride changes in the stride time) in octogenarians (G80, n = 10), 65-yr-olds (G65, n = 10), and young controls (G25, n = 10) walking on a treadmill at six different speeds. The energy cost of walking was higher for G80 than for G25 across the different walking speeds (P < 0.05). Stride time variability at preferred walking speed was significantly greater in G80 (2.31 +/- 0.68%) and G65 (1.93 +/- 0.39%) compared with G25 (1.40 +/- 0.30%; P < 0.05). There was no significant correlation between gait instability and energy cost of walking at preferred walking speed. These findings demonstrated greater energy expenditure in healthy elderly subjects while walking and increased gait instability. However, no relationship was noted between these two variables. The increase in energy cost is probably multifactorial, and our results suggest that gait instability is probably not the main contributing factor in this population. We thus concluded that other mechanisms, such as the energy expenditure associated with walking movements and related to mechanical work, or neuromuscular factors, are more likely involved in the higher cost of walking in elderly people.     

Sensitive high-performance liquid chromatographic assay for pilocarpine in biological fluids using fluorescence derivatisation

A sensitive assay for pilocarpine in biological fluids has been developed involving HPLC of a fluorescent derivative of 4-bromomethyl-7-methoxycoumarin. Pilosine as internal standard was added before the derivatisation step. The fluorescent derivatives were well resolved and separated from excess reagent and endogeneous compounds on a cyanopropyl silica column. The detection limit of pilocarpine in biological fluids was 1.0 ng/ml and the assay was linear up to a concentration of 150 ng/ml. The assay was applied to a preliminary study of pilocarpine disposition in man after a single oral dose. This is the first report of pilocarpine excretion into saliva.     

Design and applications of a self-aligning liquid junction-electrospray interface for capillary electrophoresis-mass spectrometry

A simple self-aligning liquid junction-electrospray interface for coupling a capillary electrophoresis (CE) system to an atmospheric pressure ionization (API) mass spectrometer (CE-MS) was developed. In contrast to previous liquid junction interfaces, the self-aligning liquid junction interface simplifies the precise alignment of the CE capillary and the sprayer needle and uses a positive make-up flow. Several capillary CE-MS applications were run using both the self-aligning liquid junction interface and the widely used sheath flow interface for comparison purposes. The electrospray stability of the self-aligning liquid junction interface is consistently better even when non-volatile electrolyte solutions are used. At first, some band broadening was obtained with the self-aligning liquid junction interface. Experiments with different CE buffer systems suggested that this band broadening was caused by the materials used in constructing the interface. By using a more inert material for the sprayer needle, the self-aligning liquid junction exhibits excellent electrophoretic resolution, comparable sensitivity, and higher signal-to-noise ratios when run under the same conditions as the sheath flow interface.     

Kinetic studies of electron transfer in the cyt b 5 : metHb system

 The kinetics of methemoglobin reduction by cytochrome b ₅ has been studied by stopped-flow and saturation transfer NMR. A forward rate constant k _f = 2.44×10⁴ M^–1 s^–1 and a reverse rate constant k _b = 540 M^–1s^–1 have been observed at 10 mm, pH 6.20, 25  °C. The ratio k _f/k _b = k _eq = 43.6 is in good agreement with the equilibrium constant calculated from the electrochemical potential between cyt b ₅ and methemoglobin. A bimolecular collisional mechanism is proposed for the electron transfer from cyt b ₅ to methemoglobin based on the kinetic data analysis. The dependence of the rate constants on ionic strengths supports such collisional mechanism. It is also found that the reaction rate strongly depends on the conformations of methemoglobin. Received: 20 February 1996 / Accepted: 4 June 1996