bluuebunny/crossref_metadata_2025_split huggingface dataset:
MAXTEMP: A method to maximize precision of the temporal method for estimatingNein genetic monitoring programs
Authors: Waples Robin S. , Masuda Michele M. , LaCava Melanie E.F. , Finger Amanda J. 
Published: June 2024

AbstractWe introduce a new software program,MAXTEMP, that maximizes precision of the temporal method for estimating effective population size (Ne) in genetic monitoring programs, which are increasingly used to systematically track changes in global biodiversity. Scientists and managers are typically most interested inNefor individual generations, either to match with single-generation estimates of census size (N) or to evaluate consequences of specific management actions or environmental events. Systematically sampling every generation produces a time series of single-generation estimates of temporal, which can then be used to estimateNe; however, these estimates have relatively low precision because each reflects just a single episode of genetic drift. Systematic sampling also produces an array of multigenerational temporal estimates that collectively contain a great deal of information about genetic drift that, however, can be difficult to interpret. Here we show how additional information contained in multigenerational temporal estimates can be leveraged to increase precision offor individual generations. Using information from one additional generation before and after a target generation can reduce the standard deviation ofby up to 50%, which not only tightens confidence intervals aroundbut also reduces the incidence of extreme estimates. Practical application ofMAXTEMPis illustrated with data for a long-term genetic monitoring program for California delta smelt. A second feature ofMAXTEMP, which allows one to estimateNein an unsampled generation using a combination of temporal and single-sample estimates ofNefrom sampled generations, is also described and evaluated.
Estradiol Modulates Resting-State Connectivity in Perimenopausal Depression
Authors: Hynd Megan , Gibson Kathryn , Walsh Melissa , Phillips Rachel , Prim Julianna , Eisenlohr-Moul Tory , Walsh Erin , Dichter Gabriel , Schiller Crystal 
Published: June 2024

ABSTRACTThe perimenopausal transition is marked by an increased risk for affective dysregulation and major depressive disorder (MDD), with hormone replacement therapy using estradiol (E2) showing promise for alleviating symptoms of perimenopausal-onset MDD (PO-MDD). Although E2’s effectiveness is recognized, its mechanisms underlying mood symptom modulation remain to be fully elucidated. Building on previous research suggesting that E2 may influence mood by altering cortico-subcortical connectivity, this study investigates the effects of transdermal E2 on resting-state functional connectivity (rsFC) in perimenopausal women with and without PO-MDD, focusing on rsFC changes using seed regions within emotion and reward processing networks. In this pharmaco-fMRI study, sixteen participants with PO-MDD and eighteen controls underwent rsFC analysis before and after three weeks of transdermal E2 administration. Pre-E2 results showed that the PO-MDD group, compared to controls, exhibited increased connectivity between the right amygdala (seed) and medial prefrontal cortex and anterior cingulate cortex, and decreased connectivity with the supplementary motor area. Post-E2 results revealed several significant E2-induced changes in connectivity between the PO-MDD and control groups: PO-MDD showed increased connectivity between the right caudate nucleus (seed) and left insula, and decreased connectivity between the right putamen (seed) and left hippocampus, and the right amygdala (seed) and left ventromedial prefrontal cortex. Notably, changes in connectivity were predictive of symptom trajectory across anhedonia, depressive mood, somatic, and vasomotor domains in the PO-MDD group. These findings enrich our understanding of PO-MDD by highlighting distinct rsFC patterns characteristic of the disorder and their shifts in response to E2 treatment, suggesting potential neural mechanisms underlying E2’s mood-modulating effects.
Economic evaluation of a wearable-based intervention to increase physical activity among insufficiently active middle-aged adults
Authors: Ching Jack H. , Duff Steve , Hernandez John 
Published: June 2024

AbstractBackgroundPhysical activity levels worldwide have declined over recent decades, with the average number of daily steps decreasing steadily since 1995. Given that physical inactivity is a major modifiable risk factor for chronic disease and mortality, increasing the level of physical activity is a clear opportunity to improve population health on a broad scale. The current study aims to assess the cost-effectiveness and budget impact of a Fitbit-based intervention among healthy, but insufficiently active, adults to quantify the potential clinical and economic value for a commercially insured population in the U.S.MethodsAn economic model was developed to compare physical activity levels, health outcomes, costs, and quality-adjusted life-years (QALYs) associated with usual care and a Fitbit-based inter-vention that consists of a consumer wearable device alongside goal setting and feedback features provided in a companion software application. Improvement in physical activity was measured in terms of mean daily step count. The effects of increased daily step count were characterized as reduced short-term healthcare costs and decreased incidence of chronic diseases with corresponding improvement in health utility and reduced disease costs. Published literature, standardized costing resources, and data from a National Institutes of Health-funded research program were utilized. Cost-effectiveness and budget impact analyses were performed for a hypothetical cohort of middle-aged adults.ResultsThe base case cost-effectiveness results found the Fitbit intervention to be dominant (less costly and more effective) compared to usual care. Discounted 15-year incremental costs and QALYs were -$1,257 and 0.011, respectively. In probabilistic analyses, the Fitbit intervention was dominant in 93% of simulations and either dominant or cost-effective (defined as less than $150,000/QALY gained) in 99.4% of simulations. For budget impact analyses conducted from the perspective of a U.S. Commercial payer, the Fitbit intervention was estimated to save approximately $6.5 million dollars over 2 years and $8.5 million dollars over 5 years for a cohort of 8,000 participants. Although the economic analysis results were very robust, the short-term healthcare cost savings were the most uncertain in this population and warrant further research.ConclusionsThere is abundant evidence documenting the benefits of wearable activity trackers when used to increase physical activity as measured by daily step counts. Our research provides additional health economic evidence supporting implementation of wearable-based interventions to improve population health, and offers compelling support for payers to consider including wearable-based physical activity interventions as part of a comprehensive portfolio of preventive health offerings for their insured populations.
VILOCA: Sequencing quality-aware haplotype reconstruction and mutation calling for short- and long-read data
Authors: Fuhrmann Lara , Langer Benjamin , Topolsky Ivan , Beerenwinkel Niko 
Published: June 2024

AbstractRNA viruses exist in large heterogeneous populations within their host. The structure and diversity of virus populations affects disease progression and treatment outcomes. Next-generation sequencing allows detailed viral population analysis, but inferring diversity from error-prone reads is challenging. Here, we present VILOCA, a method for mutation calling and reconstruction of local haplotypes from short- and long-read viral sequencing data. Local haplotypes refer to genomic regions that have approximately the length of the input reads. VILOCA recovers local haplotypes by using a Dirichlet process mixture model to cluster reads around their unobserved haplotypes and leveraging quality scores of the sequencing reads. We assessed the performance of VILOCA in terms of mutation calling and haplotype reconstruction accuracy on simulated and experimental Illumina, PacBio, and Oxford Nanopore data. On simulated and experimental Illumina data, VILOCA performed better or similar to existing methods. On the simulated long-read data, VILOCA is able to recover on average 82% of the ground truth mutations with perfect precision compared to only 64% recall and 90% precision of the second-best method. In summary, VILOCA provides significantly improved accuracy in mutation and haplotype calling, especially for long-read sequencing data, and therefore facilitates the comprehensive characterization of heterogeneous within-host viral populations.
Beyond Pre-Post Surveys: Exploring Validity Evidence For The Use Of Experience Sampling Methods To Measure Student Anxiety In Introductory Biology
Authors: Weatherton Maryrose , Rosenberg Joshua M. , Rocconi Louis , Schussler Elisabeth E. 
Published: June 2024

AbstractClassroom experiences elicit many emotions in students. Of these emotions, anxiety, or the feeling of uncertainty about a prospective event, has outsized impacts on students’ academic achievement and persistence. To understand the effects of student anxiety on student outcomes, education researchers often utilize single or dual-time point (e.g., pre-post) surveys. However, we posit that these methods have significant limitations, including the potential to miss variation in student emotions across time. One methodological solution to this problem is using experience sampling methods (ESM), or short, frequent surveys that capture student experiences as they occur. This study sought to provide evidence of validity for the use of ESM to measure student anxiety in Introductory Biology courses. We compared student anxiety data gathered via ESM and traditional survey methods (i.e., pre-post surveys) in terms of 1) differences in participant recruitment, 2) students’ experience of anxiety, and 3) the predictive ability on end-of-course outcomes. Our results revealed that: 1) Compared to non-ESM participants, the ESM group has significantly fewer men and had significantly higher perceptions of instructor support, 2) Average anxiety levels measured via ESM were lower and more variable than those measured via pre-post surveys, and 3) Post-survey measures of anxiety and average ESM measures of anxiety significantly predicted students’ final grade. We discuss the implications of these results for future applications of ESM and pre-post survey methods; specifically, we propose that ESM methods may be more advantageous than pre-post surveys in cases where researchers aim to understand intra-individual processes, like emotions.
Model-Based Assessment of Photoplethysmogram Signal Quality in Real-Life Environments
Authors: Su Yan-Wei , Hao Chia-Cheng , Liu Gi-Ren , Sheu Yuan-Chung , Wu Hau-Tieng 
Published: June 2024

AbstractAssessing signal quality is crucial for photoplethysmogram analysis, yet a precise mathematical model for defining signal quality is often lacking, posing challenges in the quantitative analysis. To tackle this problem, we propose a Signal Quality Index (SQI) based on the adaptive non-harmonic model (ANHM) and a Signal Quality Assessment (SQA) model, which is trained using the boosting learning algorithm. The effectiveness of the proposed SQA model is tested on publicly available databases with experts’ annotations. Result: The DaLiA database [20] is used to train the SQA model, which achieves favorable accuracy and macro-F1 scores in other public databases (accuracy 0.83, 0.76 and 0.87 and macro-F1 0.81, 0.75 and 0.87 for DaLiA-testing dataset, TROIKA dataset [31], and WESAD dataset [23], respectively). This preliminary result shows that the ANHM model and the model-based SQI have potential for establishing an interpretable SQA system.
A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)
Authors: Kurmi Yashwant , Viswanathan Malvika , Zu Zhongliang 
Published: June 2024

ABSTRACTPurposeTo develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods.MethodThe DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback–Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric.ResultsIn digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings.ConclusionThe DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared to other methods.
Loss of ARID1A accelerates prostate tumourigenesis with a proliferative collagen-poor phenotype through co-operation with AP1 subunit cFos
Authors: Hartley Andrew , Galbraith Laura C.A. , Shaw Robin , Tibbo Amy , Veeratterapillay Rajan , Wilson Laura , Heer Rakesh , Blyth Karen , Leung Hing , Ahmad Imran 
Published: June 2024

AbstractProstate cancer (PC) is the most common male visceral cancer, and second leading cause of cancer mortality in men in the Western world. Using a forward-mutagenesis Sleeping Beauty (SB) transposon-based screen in a Probasin Cre-Recombinase (Pb-Cre)Pten-deficient mouse model of PC, we identifiedArid1aloss as a driver in the development of metastatic disease. The insertion of transposon in theArid1agene resulted in a 60% reduction ofArid1aexpression, and reduced tumour free survival (SB:Ptenfl/flArid1aINTmedian 226 days vsSB:Ptenfl/flArid1aWT293 days, p=0.02),with elevated rates of metastasis (SB:Ptenfl/flArid1aINT75% lung metastasis rate vs 17%SB:Ptenfl/flArid1aWT,p<0.001 ). We further generated aPb-Cre Pten- andArid1a-deficient mouse model, in which loss ofArid1ademonstrated a profound acceleration in tumorigenesis inPtenfl/flmice compared toPtenloss alone (Pb-Cre Ptenfl/flArid1a+/+median survival of 267 days vs Pb-CrePtenfl/flArid1afl/fl103 days, p<0.0001). Our data revealed homozygousArid1aloss is required to dramatically accelerate prostate tumourigenesis, resulting in tumours with a less differentiated phenotype and a disorganised stroma. Furthermore,Arid1aloss mediated tumour formation in the mouse involved both the anterior and dorsolateral lobes, a unique feature fromPten-loss and other reported PC GEMM where tumour formation tends to be limited to the anterior lobes. Analysis of RNA and ChIP -Sequencing data suggestsArid1aloss enhanced the function of AP-1 subunit cFos. In clinical PC cohort, ARID1A and cFos levels stratified an aggressive subset of PC with a poor survival outcome with a median of only 30 months.
The Untapped Potential of Tree Size in Reconstructing Evolutionary and Epidemiological Dynamics
Authors: MacPherson Ailene , Pennell Matt 
Published: June 2024

AbstractA phylogenetic tree has three types of attributes: size, shape (topology), and branch lengths. Phylody-namic studies are often motivated by questions regarding the size of clades, nevertheless, nearly all of the inference methods only make use of the other two attributes. In this paper, we ask whether there is additional information if we consider tree size more explicitly in phylodynamic inference methods. To address this question, we first needed to be able to compute the expected tree size distribution under a specified phylodynamic model; perhaps surprisingly, there is not a general method for doing so — it is known what this is under a Yule or constant rate birth-death model but not for the more complicated scenarios researchers are often interested in. We present three different solutions to this problem: using i) the deterministic limit; ii) master equations; and iii) an ensemble moment approximation. Using simulations, we evaluate the accuracy of these three approaches under a variety of scenarios and alternative measures of tree size (i.e., sampling through time or only at the present; sampling ancestors or not). We then use the most accurate measures for the situation, to investigate the added informational content of tree size. We find that for two critical phylodynamic questions — i) is diversification diversity dependent? and, ii) can we distinguish between alternative diversification scenarios? — knowing the expected tree size distribution under the specified scenario provides insights that could not be gleaned from considering the expected shape and branch lengths alone. The contribution of this paper is both a novel set of methods for computing tree size distributions and a path forward for richer phylodynamic inference into the evolutionary and epidemiological processes that shape lineage trees.
Contingencies in biofilm adaptation ofMycobacterium tuberculosis
Authors: Kernien John F. , Youngblom Madison A. , Smith Tracy M. , Fry Sydney S. , Mohamed Mohamed A. , Murray Holly J. , Lawrence Kadee N. , Pepperell Caitlin S. 
Published: June 2024

AbstractBiofilms are structured microbial communities that offer protection from a range of environmental stressors. Studies of experimental evolution within biofilms have yielded important insights into mechanisms of biofilm formation, as well as fundamental principles governing bacterial adaptation within these structured communities. Building on research using tractable species, our lab created a model for studying biofilm adaptation inMycobacterium tuberculosis (M. tb),a fastidious, slow growing and lethal pathogen of humans. Here, we evolved eighteenM. tbpopulations arising from six parental genetic backgrounds under biofilm selection to investigate diversity in mechanisms ofM. tbbiofilm adaptation. We found that fine-scale differences among strains at the initiation of the experiment influenced the degree of replicability in their evolution. Adaptive paths were highly parallel for some strains, whereas others evolved distinct mutations across iterations of the experiment. Our data suggest that differences in replicability arise from mutational biases and variable fitness impacts of mutations across genetic backgrounds. Comparison of our results with genomic data fromM. tbpopulations within hosts with tuberculosis (TB) revealed that several mutations associated with biofilm selection are also among the most common to emerge during natural infection. These biofilm-associated variants are not maintained in naturalM. tbpopulations, suggesting that biofilm selection in our model mimics selection pressures that are transiently encountered byM. tbduring specific phases of infection. Overall, these results support development of biofilm directed therapies for TB and demonstrate the importance of subtle genetic variation in shapingM. tbresponses to changing selection pressures.SignificanceMycobacterium tuberculosis (M. tb),the causative agent of tuberculosis (TB), a difficult-to-treat, persistent infection with high mortality. One cause of this persistence is the ability ofM. tbto form biofilms, aggregated structures capable of resisting antibiotics and host defenses. Here, we used an evolutionary model to investigate mechanisms ofM. tbbiofilm formation. We found adaptation to biofilm growth to be affected by mutational biases and interactions among mutations. Our simple in vitro model appears to mimic aspects of natural infection, as identical mutations emerge in the laboratory under biofilm selection and within hosts with TB. These results expand our knowledge ofM. tbbiofilm development and inform our understanding of how this bacterium responds to novel selection pressures.
Lower-limb coordination changes following a six-week training intervention that elicited enhancements to maximum velocity sprint performance
Authors: Lenthall Daniel , Brazil Adam , Castaño-Zambudio Adrián , Lightfoot Harry , Mendiguchia Jurdan , Jiménez-Reyes Pedro , Colyer Steffi L. 
Published: June 2024

ABSTRACTAlterations to intra- and inter-limb coordination with improved maximal velocity performance remain largely unexplored. This study quantified within-day variability in lower-limb segmental coordination profiles during maximal velocity sprinting and investigated the modifications to coordination strategies in 15 recreationally active males following a six-week period comprised of a multimodal training programme (intervention group (INT); n = 7) or continued participation in sports (control group; n = 8). The INT demonstrated a large decline (effect size = -1.54) in within-day coordination profile variability, suggesting potential skill development. Thigh-thigh coordination modifications for the INT were characterised by an earlier onset of trail thigh reversal in early swing (26 vs. 28% stride) and lead thigh reversal in late swing (76 vs. 79% stride), rather than increases in overall time spent in anti-phase. Moreover, an increase in backwards thigh-dominant, thigh-shank (effect size, 95% CIs: 0.75, 0.17 to 1.33) and shank-dominant, shank-foot (0.76, -0.17 to 1.68) rotations during late swing likely facilitated more aggressive acceleration of the foot prior to touchdown, contributing to reduced touchdown distance and more favourable lower-limb configuration at initial ground contact. These novel findings provide empirical support for the role of longitudinal coordination modifications in improving maximal velocity performance.SUMMARY STATEMENTCoordination during the swing phase was more modifiable than during stance, with earlier reversal of antiphase thigh-thigh and backwards thigh-shank and shank-foot rotations in late swing observed with improved performance.