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PeerJ 2020Bayesian analyses offer many benefits for phylogenetic, and have been popular for analysis of amino acid alignments. It is necessary to specify a substitution and site...
BACKGROUND
Bayesian analyses offer many benefits for phylogenetic, and have been popular for analysis of amino acid alignments. It is necessary to specify a substitution and site model for such analyses, and often an ad hoc, or likelihood based method is employed for choosing these models that are typically of no interest to the analysis overall.
METHODS
We present a method called OBAMA that averages over substitution models and site models, thus letting the data inform model choices and taking model uncertainty into account. It uses trans-dimensional Markov Chain Monte Carlo (MCMC) proposals to switch between various empirical substitution models for amino acids such as Dayhoff, WAG, and JTT. Furthermore, it switches base frequencies from these substitution models or use base frequencies estimated based on the alignment. Finally, it switches between using gamma rate heterogeneity or not, and between using a proportion of invariable sites or not.
RESULTS
We show that the model performs well in a simulation study. By using appropriate priors, we demonstrate both proportion of invariable sites and the shape parameter for gamma rate heterogeneity can be estimated. The OBAMA method allows taking in account model uncertainty, thus reducing bias in phylogenetic estimates. The method is implemented in the OBAMA package in BEAST 2, which is open source licensed under LGPL and allows joint tree inference under a wide range of models.
PubMed: 32832259
DOI: 10.7717/peerj.9460 -
Affective Science Mar 2024Many studies in affective neuroscience rely on statistical procedures designed to estimate population averages and base their main conclusions on group averages.... (Review)
Review
Many studies in affective neuroscience rely on statistical procedures designed to estimate population averages and base their main conclusions on group averages. However, the obvious unit of analysis in affective neuroscience is the individual, not the group, because emotions are individual phenomena that typically vary across individuals. Conclusions based on group averages may therefore be misleading or wrong, if interpreted as statements about emotions of an individual, or meaningless, if interpreted as statements about the group, which has no emotions. We therefore advocate the Single-N design as the default strategy in research on emotions, testing one or several individuals extensively with the primary purpose of obtaining results at the individual level. In neuroscience, the equivalent to the Single-N design is deep imaging, the emerging trend of extensive measurements of activity in single brains. Apart from the fact that individuals react differently to emotional stimuli, they also vary in shape and size of their brains. Group-based analysis of brain imaging data therefore refers to an "average brain" that was activated in a way that may not be representative of the physiology of any of the tested individual brains, nor of how these brains responded to the experimental stimuli. Deep imaging avoids such group-averaging artifacts by simply focusing on the individual brain. This methodological shift toward individual analysis has already opened new research areas in fields like vision science. Inspired by this, we call for a corresponding shift in affective neuroscience, away from group averages, and toward experimental designs targeting the individual.
PubMed: 38495781
DOI: 10.1007/s42761-023-00182-5 -
Journal of the Canadian Association of... Dec 2021To determine representation of women in gastroenterology (GI) at residency and leadership levels in Canada.
BACKGROUND
To determine representation of women in gastroenterology (GI) at residency and leadership levels in Canada.
METHODS
The Canadian Resident Matching Service provided data for internal medicine (IM), general surgery (GS), GI and cardiology applicant cycles 2014 to 2018. -tests were used to compare proportion of women entering each residency program. An internet search was conducted to calculate percentages of women as GI association presidents, residency program directors, division heads and oral speakers at conferences.
RESULTS
IM residency had on average of 1789 applicants with 487 matched (49.4% versus 49.5% women). GS residency had on average 357 applicants with 90 matched (41% versus 54.4% women). GI residency had on average 46 applicants with 34 matched (37% versus 35.3% women). Cardiology residency had on average 76 applicants with 54 matched (29% versus 27.8% women).The Canadian Association of Gastroenterology (CAG) has had two out of 47 (4.2%) women presidents. The Ontario Association of Gastroenterology (OAG) has had no women presidents (0/9). The Association des gastro-entérologues du Québec (AGEQ) has had two out of 15 (13%) women presidents. The Alberta Society of Gastroenterology (ASG) has had one out of five (20%) women presidents. From 2018 to 2020, university division heads ranged from 0% to 13.3% women (0 to 2/15). University GI training program directors ranged from 28.6% to 35.7% (4 to 5/14). Women speakers at CAG's annual conference varied 27% to 42% from 2016 to 2020, averaging 32.7%. Women speakers at OAG's, AGEQ's and ASG's annual conferences averaged 23.3%, 24.1% and 35%, respectively.
CONCLUSION
Women gastroenterologists display low representation at multiple levels along the GI career pathway.
PubMed: 34877463
DOI: 10.1093/jcag/gwab020 -
Water Research Jun 2020The degree to which a technology used for drinking water treatment physically removes or inactivates pathogenic microorganisms is commonly expressed as a log-reduction...
The degree to which a technology used for drinking water treatment physically removes or inactivates pathogenic microorganisms is commonly expressed as a log-reduction (or log-removal) and is of central importance to the provision of microbiologically safe drinking water. Many evaluations of water treatment process performance generate or compile multiple values of microorganism log-reduction, and it is common to report the average of these log-reduction values as a summary statistic. This work provides a cautionary note against misinterpretation and misuse of averaged log-reduction values by mathematically proving that the average of a set of log-reduction values characteristically overstates the average performance of which the set of log-reduction values is believed to be representative. This has two important consequences for drinking water and food safety as well as other applications of log-reduction: 1) a technology with higher average log-reduction does not necessarily have higher average performance, and 2) risk analyses using averaged log-reduction values as point estimates of treatment efficiency will underestimate average risk-sometimes by well over an order of magnitude. When analyzing a set of log-reduction values, a summary statistic called the effective log-reduction (which averages reduction or passage rates and expresses this as a log-reduction) provides a better representation of average performance of a treatment technology.
Topics: Drinking Water; Water Purification
PubMed: 32247998
DOI: 10.1016/j.watres.2020.115702 -
PLoS Computational Biology Apr 2024Trial-averaged metrics, e.g. tuning curves or population response vectors, are a ubiquitous way of characterizing neuronal activity. But how relevant are such...
Trial-averaged metrics, e.g. tuning curves or population response vectors, are a ubiquitous way of characterizing neuronal activity. But how relevant are such trial-averaged responses to neuronal computation itself? Here we present a simple test to estimate whether average responses reflect aspects of neuronal activity that contribute to neuronal processing. The test probes two assumptions implicitly made whenever average metrics are treated as meaningful representations of neuronal activity: Reliability: Neuronal responses repeat consistently enough across trials that they convey a recognizable reflection of the average response to downstream regions.Behavioural relevance: If a single-trial response is more similar to the average template, it is more likely to evoke correct behavioural responses. We apply this test to two data sets: (1) Two-photon recordings in primary somatosensory cortices (S1 and S2) of mice trained to detect optogenetic stimulation in S1; and (2) Electrophysiological recordings from 71 brain areas in mice performing a contrast discrimination task. Under the highly controlled settings of Data set 1, both assumptions were largely fulfilled. In contrast, the less restrictive paradigm of Data set 2 met neither assumption. Simulations predict that the larger diversity of neuronal response preferences, rather than higher cross-trial reliability, drives the better performance of Data set 1. We conclude that when behaviour is less tightly restricted, average responses do not seem particularly relevant to neuronal computation, potentially because information is encoded more dynamically. Most importantly, we encourage researchers to apply this simple test of computational relevance whenever using trial-averaged neuronal metrics, in order to gauge how representative cross-trial averages are in a given context.
Topics: Animals; Mice; Neurosciences; Neurons; Somatosensory Cortex; Models, Neurological; Optogenetics; Computational Biology; Reproducibility of Results; Computer Simulation
PubMed: 38640119
DOI: 10.1371/journal.pcbi.1012000 -
Biophysical Journal Jan 2021Molecular motors couple chemical transitions to conformational changes that perform mechanical work in a wide variety of biological processes. Disruption of this...
Molecular motors couple chemical transitions to conformational changes that perform mechanical work in a wide variety of biological processes. Disruption of this coupling can lead to diseases, and therefore there is a need to accurately measure mechanochemical coupling in motors in both health and disease. Optical tweezers with nanometer spatial and millisecond temporal resolution have provided valuable insights into these processes. However, fluctuations due to Brownian motion can make it difficult to precisely resolve these conformational changes. One powerful analysis technique that has improved our ability to accurately measure mechanochemical coupling in motor proteins is ensemble averaging of individual trajectories. Here, we present a user-friendly computational tool, Software for Precise Analysis of Single Molecules (SPASM), for generating ensemble averages of single-molecule data. This tool utilizes several conceptual advances, including optimized procedures for identifying single-molecule interactions and the implementation of a change-point algorithm, to more precisely resolve molecular transitions. Using both simulated and experimental data, we demonstrate that these advances allow for accurate determination of the mechanics and kinetics of the myosin working stroke with a smaller set of data. Importantly, we provide our open-source MATLAB-based program with a graphical user interface that enables others to readily apply these advances to the analysis of their own data.
Topics: Kinesins; Kinetics; Myosins; Nanotechnology; Optical Tweezers
PubMed: 33248132
DOI: 10.1016/j.bpj.2020.10.047 -
Frontiers in Artificial Intelligence 2021Deep neural networks (DNNs) are typically trained using the conventional stochastic gradient descent (SGD) algorithm. However, SGD performs poorly when applied to train...
Deep neural networks (DNNs) are typically trained using the conventional stochastic gradient descent (SGD) algorithm. However, SGD performs poorly when applied to train networks on non-ideal analog hardware composed of resistive device arrays with non-symmetric conductance modulation characteristics. Recently we proposed a new algorithm, the Tiki-Taka algorithm, that overcomes this stringent symmetry requirement. Here we build on top of Tiki-Taka and describe a more robust algorithm that further relaxes other stringent hardware requirements. This more robust second version of the Tiki-Taka algorithm (referred to as TTv2) 1. decreases the number of device conductance states requirement from 1000s of states to only 10s of states, 2. increases the noise tolerance to the device conductance modulations by about 100x, and 3. increases the noise tolerance to the matrix-vector multiplication performed by the analog arrays by about 10x. Empirical simulation results show that TTv2 can train various neural networks close to their ideal accuracy even at extremely noisy hardware settings. TTv2 achieves these capabilities by complementing the original Tiki-Taka algorithm with lightweight and low computational complexity digital filtering operations performed outside the analog arrays. Therefore, the implementation cost of TTv2 compared to SGD and Tiki-Taka is minimal, and it maintains the usual power and speed benefits of using analog hardware for training workloads. Here we also show how to extract the neural network from the analog hardware once the training is complete for further model deployment. Similar to Bayesian model averaging, we form analog hardware compatible averages over the neural network weights derived from TTv2 iterates. This model average then can be transferred to another analog or digital hardware with notable improvements in test accuracy, transcending the trained model itself. In short, we describe an end-to-end training and model extraction technique for extremely noisy crossbar-based analog hardware that can be used to accelerate DNN training workloads and match the performance of full-precision SGD.
PubMed: 34568813
DOI: 10.3389/frai.2021.699148 -
Cureus Jan 2023Introduction YouTube, an unregulated video-sharing website, is the second most visited website on the internet. As more patients turn to the internet for information...
Introduction YouTube, an unregulated video-sharing website, is the second most visited website on the internet. As more patients turn to the internet for information about colon cancer screening, it is important to understand what they are consuming online. Our goal was to evaluate YouTube videos about colon cancer screening to better understand the information patients are accessing. Methods We searched YouTube on October 28, 2020, using the following search terms sorted by relevance and view count: colonoscopy, colon cancer screening, virtual colonoscopy, colonoscopy alternatives, and cologuard. Videos longer than 10 minutes, not in English, and duplicates were excluded. Three evaluators graded each video using the DISCERN criteria. Numerical data were averaged into a composite score. Two-sided t-tests and one-way ANOVA tests were used to compare mean ratings between groups. Results Fifty videos were analyzed, with a total of 23,148,938 views, averaging 462,979 views per video. The average overall rating was 3.16/5. There was no difference between search methods, search terms, or presence of a physician. The average ratings for videos with gastroenterologists (3.08), other physicians (3.35), and non-physicians (3.09) were not significantly different. Videos without physicians had more views on average (1,148,677) compared to videos with gastroenterologists (157,846, p=0.013) or other physicians (35,730, p=0.013). Conclusion YouTube videos related to colon cancer screening were of good quality regardless of search terms, search methods, or presence of a physician. However, videos without physicians were viewed more frequently. Physicians should continue making videos that address deficits while increasing viewership.
PubMed: 36788914
DOI: 10.7759/cureus.33684 -
Statistical Methods in Medical Research Sep 2023Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically,...
Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc. Inevitably the amount of information per Lexis diminishes with increasing stratification. Several methods have been proposed to smooth observed Lexis diagrams up front to clarify salient patterns and improve summary estimates of averages, gradients, and trends. In this article, we develop a novel bivariate kernel-based smoother that incorporates two key innovations. First, for any given kernel, we calculate its singular values decomposition, and select an optimal truncation point-the number of leading singular vectors to retain-based on the bias-corrected Akaike information criterion. Second, we model-average over a panel of candidate kernels with diverse shapes and bandwidths. The truncated model averaging approach is fast, automatic, has excellent performance, and provides a variance-covariance matrix that takes model selection into account. We present an in-depth case study (invasive estrogen receptor-negative breast cancer incidence among non-Hispanic white women in the United States) and simulate operating characteristics for 20 representative cancers. The truncated model averaging approach consistently outperforms any fixed kernel. Our results support the routine use of the truncated model averaging approach in descriptive studies of cancer.
Topics: Humans; Female; United States; Breast Neoplasms; Incidence
PubMed: 37621099
DOI: 10.1177/09622802231192950 -
Ultrasound in Obstetrics & Gynecology :... Oct 1999To estimate the umbilical artery and vein blood volume flow using B-mode and Doppler ultrasound in the second and third trimesters of pregnancy.
OBJECTIVE
To estimate the umbilical artery and vein blood volume flow using B-mode and Doppler ultrasound in the second and third trimesters of pregnancy.
DESIGN
This was a cross-sectional study of 129 singleton, healthy pregnancies at 23-33 weeks' gestation. The umbilical artery and vein cross-sectional area, time-averaged velocity and pulsatility index were measured in a free loop of cord, and the fetal weight was estimated. Ranges for each parameter were obtained; from these the blood flow for the vein and artery was calculated, and the average flow corrected for fetal weight was derived.
RESULTS
The median time for examination was 6 min. The mean cross-sectional area and time-averaged velocity for both the vein and artery increased linearly with gestation. The umbilical artery flow correlated closely with the average vein flow (r = 0.9, p < 0.001). There was a significant, though poor, inverse correlation between the umbilical artery pulsatility index and the average umbilical flow (r = -0.25, p < 0.05). The average umbilical flow (calculated from the mean of arterial and venous flow), corrected for estimated fetal weight, decreased from 189.2 ml/kg per min at 23 weeks to 176.2 ml/kg per min at 33 weeks' gestation.
CONCLUSION
The estimates of fetal umbilical flow obtained by this Doppler method are consistent with previously published data. Averaging the arterial and venous flow is theoretically advantageous in reducing the inherent errors in estimating either the arterial or the venous flow. This method of measuring umbilical flow may have clinical potential in assessing fetal health and disease processes.
Topics: Blood Flow Velocity; Cross-Sectional Studies; Female; Humans; Pregnancy; Pulsatile Flow; Time Factors; Ultrasonography, Doppler, Color; Ultrasonography, Interventional; Ultrasonography, Prenatal; Umbilical Arteries; Umbilical Veins
PubMed: 10586476
DOI: 10.1046/j.1469-0705.1999.14040250.x