bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting myeloid-derived suppressor cells in combination with tumor cell vaccination predicts anti-tumor immunity and breast cancer dormancy: an in silico experiment
Authors: Mehdizadeh Reza , Shariatpanahi Seyed Peyman , Goliaei Bahram , Rüegg Curzio 
Published: April 2023

AbstractAmong the different breast cancer subsets, triple-negative breast cancer (TNBC) has the worst prognosis and limited options for targeted therapies. Immunotherapies are emerging as novel treatment opportunities for TNBC. However, the surging immune response elicited by immunotherapies to eradicate cancer cells can select resistant cancer cells, which may result in immune escape and tumor evolution and progression. Alternatively, maintaining the equilibrium phase of the immune response may be advantageous for keeping a long-term immune response in the presence of a small-size residual tumor. Myeloid-derived suppressor cells (MDSCs) are activated, expanded, and recruited to the tumor microenvironment by tumor-derived signals and can shape a pro-tumorigenic micro-environment by suppressing the innate and adaptive anti-tumor immune responses. We recently proposed a model describing immune-mediated breast cancer dormancy instigated by a vaccine consisting of dormant, immunogenic breast cancer cells derived from the murine 4T1 TNBC-like cell line. Strikingly, these 4T1-derived dormant cells recruited fewer MDSCs compared to aggressive 4T1 cells. Recent experimental studies demonstrated that inactivating MDSCs has a profound impact on reconstituting immune surveillance against the tumor. Here, we developed a deterministic mathematical model for simulating MDSCs depletion from mice bearing aggressive 4T1 tumors resulting in immunomodulation. Our computational simulations indicate that a vaccination strategy with a small number of tumor cells in combination with MDSC depletion can elicit an effective immune response suppressing the growth of a subsequent challenge with aggressive tumor cells, resulting in sustained tumor dormancy. The results predict a novel therapeutic opportunity based on the induction of effective anti-tumor immunity and tumor dormancy.
Natural statistics of human head orientation constrain models of vestibular processing
Authors: Sinnott Christian B. , Hausamann Peter A. , MacNeilage Paul R. 
Published: April 2023

AbstractHead orientation relative to gravity determines how gravity-dependent environmental structure is sampled by the visual system, as well as how gravity itself is sampled by the vestibular system. Therefore, both visual and vestibular sensory processing should be shaped by the statistics of head orientation relative to gravity. Here we report the statistics of human head orientation during unconstrained natural activities in humans for the first time, and we explore implications for models of vestibular processing. We find that the distribution of head pitch is more variable than head roll and that the head pitch distribution is asymmetrical with an over-representation of downward head pitch, consistent with ground-looking behavior. We further suggest that pitch and roll distributions can be used as empirical priors in a Bayesian framework to explain previously measured biases in perception of both roll and pitch. Gravitational and inertial acceleration stimulate the otoliths in an equivalent manner, so we also analyze the dynamics of human head orientation to better understand how knowledge of these dynamics can constrain solutions to the problem of gravitoinertial ambiguity. Gravitational acceleration dominates at low frequencies and inertial acceleration dominates at higher frequencies. The change in relative power of gravitational and inertial components as a function of frequency places empirical constraints on dynamic models of vestibular processing, including both frequency segregation and probabilistic internal model accounts. We conclude with a discussion of methodological considerations and scientific and applied domains that will benefit from continued measurement and analysis of natural head movements moving forward.
Diagnostic accuracy of transthoracic echocardiography for the identification of proximal aortic dissection: a systematic review and meta-analysis
Authors: Sutarjono Bayu , Ahmed Abrar Justin , Ivanova Anna , Buchel Brandon , Rauscher Joseph , O’Connell Alanna , Riekena Jeremy , Gift Aluko , Kessel Matthew , Grewal Ekjot 
Published: April 2023

AbstractThis systematic review and meta-analysis evaluated the performance of transthoracic echocardiography (TTE) for diagnosis of proximal aortic dissections based on the identification of specific sonographic features. A systematic literature search of major databases was conducted on human studies investigating the diagnostic accuracy of TTE for proximal aortic dissection. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The quality of studies was evaluated using Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data were gathered for the following sonographic findings: intimal flap, tear, or intramural hematoma; enlargement of aortic root or widening of aortic walls; aortic valve regurgitation; or pericardial effusion. Sensitivity, specificity, diagnostic odds ratio, number needed to diagnose values, and likelihood ratios were determined. Fourteen studies were included in our final analysis. More than half of the included studies demonstrated low risk of bias. The identification of intimal flap, tear, or intramural hematoma was shown to have an exceptional ability as a diagnostic tool to rule in proximal aortic dissections. TTE should be considered during the initial evaluation of patients presenting to the emergency department with suspected proximal aortic dissection. Positive sonographic findings on TTE may aid in rapid assessment, coordination of care, and treatment of individuals awaiting advanced imaging.
Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions
Authors: Oltmer Jan , Rosenblum Emma W. , Williams Emily M. , Roy Jessica , Llamas-Rodriguez Josué , Perosa Valentina , Champion Samantha N. , Frosch Matthew P. , Augustinack Jean C. 
Published: April 2023

AbstractHippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hippocampal atrophy have been a marker for the progression of Alzheimer’s disease. Relatively few studies have examined neuronal loss in the human brain using stereology. We characterize an automated high-throughput deep learning pipeline to segment hippocampal pyramidal neurons, generate pyramidal neuron estimates within the human hippocampal subfields, and relate our results to stereology neuron counts. Based on seven cases and 168 partitions, we vet deep learning parameters to segment hippocampal pyramidal neurons from the background using the open-source CellPose algorithm, and show the automated removal of false-positive segmentations. There was no difference in Dice scores between neurons segmented by the deep learning pipeline and manual segmentations (Independent Samples t-Test: t(28) = 0.33, p = 0.742). Deep-learning neuron estimates strongly correlate with manual stereological counts per subregion (Spearman’s correlation (n = 9): r(7) = 0.97, p < 0.001), and for each partition individually (Spearman’s correlation (n = 168): r(166) = 0.90, p <0 .001). The high-throughput deep-learning pipeline provides validation to existing standards. This deep learning approach may benefit future studies in tracking baseline and resilient healthy aging to the earliest disease progression.
Wind-current feedback is an energy sink for oceanic internal waves
Authors: Delpech Audrey , Barkan Roy , Renault Lionel , McWilliams James , Siyanbola Oladeji Q. , Buijsman Maarten C. , Arbic Brian K. 
Published: April 2023

AbstractInternal waves contain a large amount of energy in the ocean and are an important source of turbulent mixing. Ocean mixing is relevant for climate because it drives vertical transport of water, heat, carbon and other tracers. Understanding the life cycle of internal waves, from generation to dissipation, is therefore important for improving the representation of ocean mixing in climate models. Here, we provide evidence from a regional realistic numerical simulation in the northeastern Pacific that the wind can play an important role in damping internal waves through current feedback. This results in a reduction of 67% of wind power input at near-inertial frequencies in the region of study. Wind-current feedback also provides a net energy sink for internal tides, removing energy at a rate of 0.2 mW/m$$^2$$

2

on average, corresponding to 8% of the local internal tide generation at the Mendocino ridge. The temporal variability and modal distribution of this energy sink are also investigated.
A study on the differential of solid lung adenocarcinoma and tuberculous granuloma nodules in CT images by Radiomics machine learning
Authors: Tan Huibin , Wang Ye , Jiang Yuanliang , Li Hanhan , You Tao , Fu Tingting , Peng Jiaheng , Tan Yuxi , Lu Ran , Peng Biwen , Huang Wencai , Xiong Fei 
Published: April 2023

AbstractTo study the classification efficiency of using texture feature machine learning method in distinguishing solid lung adenocarcinoma (SADC) and tuberculous granulomatous nodules (TGN) that appear as solid nodules (SN) in non-enhanced CT images. 200 patients with SADC and TGN who underwent thoracic non-enhanced CT examination from January 2012 to October 2019 were included in the study, 490 texture eigenvalues of 6 categories were extracted from the lesions in the non-enhanced CT images of these patients for machine learning, the classification prediction model is established by using relatively the best classifier selected according to the fitting degree of learning curve in the process of machine learning, and the effectiveness of the model was tested and verified. The logistic regression model of clinical data (including demographic data and CT parameters and CT signs of solitary nodules) was used for comparison. The prediction model of clinical data was established by logistic regression, and the classifier was established by machine learning of radiologic texture features. The area under the curve was 0.82 and 0.65 for the prediction model based on clinical CT and only CT parameters and CT signs, and 0.870 based on Radiomics characteristics. The machine learning prediction model developed by us can improve the differentiation efficiency of SADC and TGN with SN, and provide appropriate support for treatment decisions.
Equivalence partition based morphological similarity clustering for large-scale time series
Authors: Hu Shaolin 
Published: April 2023

AbstractData clustering belongs to the category of unsupervised learning and plays an important role in the dynamic systems and big data. The clustering problem of sampled time-series data is undoubtedly much more challenging than that of repeatable sampling data. Most of the existing time-series clustering methods stay at the level of algorithm design, lacking rigorous theoretical foundation and being inefficient in dealing with large-scale time series. To address this issue, in this paper, we establish the mathematical theory for the large-scale time series clustering of dynamic system. The main contributions of this paper include proposing the concept of time series morphological isomorphism, proving that translation isomorphism and stretching isomorphism are equivalent relations, developing the calculation method of morphological similarity measure, and establishing a new time series clustering method based on equivalent partition and morphological similarity. These contributions provide a new theoretical foundation and practical method for the clustering of large-scale time series. Simulation results in typical applications verify the validity and practicability of the aforementioned clustering methods.
Obesity and COVID-19 mortality are correlated
Authors: Arulanandam Bernard , Beladi Hamid , Chakrabarti Avik 
Published: April 2023

AbstractIn view of a conspicuous absence of any cross-country study linking obesity and COVID-19 mortality, we conduct an empirical analysis of plausible associations between COVID-19 mortality and the proportion of obese in the adult population distributed across 142 countries around the globe. We observe a statistically significant positive association between COVID-19 mortality and the proportion of obese in adult populations spanning 142 countries. This association holds across countries belonging to different income groups and is not sensitive to a population’s median age, proportion of the elderly, and/or proportion of females. The estimated elasticity of COVID-19 mortality, with respect to the proportion of obese in adult populations, is the highest for the sub-sample of countries that belong to the high-income group. While limits of confidence intervals around the point estimates of these elasticities range between 0.7 and 2.1, on an average, every percentage point increment in the proportion of obese in adult populations contributes to an additional 1.5% points to COVID-19 mortality for high income countries. A positive association, observed between COVID-19 mortality and the proportion of the obese in a country’s adult population, is robust subject to alterations in the conditioning information set on age, gender, and income.
Developmental Language Disorder Terminology: A Survey of Speech-Language Pathologists' Use and Knowledge
Authors: Steffes Erin , Finestack Lizbeth H. 
Published: April 2023

Purpose:
Developmental language disorder (DLD) is a relatively new, internationally promoted term to describe individuals with language impairments not secondary to a biomedical condition. This study aimed to better understand speech-language pathologists' (SLPs') current level of comfort using DLD terminology and knowledge of DLD in the United States to help SLPs better understand how and why they should consider adopting DLD terminology in their clinical practice.

Method:
After completing an online presurvey to evaluate current comfort levels in using DLD terminology and current knowledge of DLD, currently practicing SLPs viewed a 45-min prerecorded educational video on DLD. Following this viewing, participants completed a postsurvey nearly identical to the presurvey to measure change in their comfort levels with DLD terminology use and in DLD knowledge.

Results:

After filtering to remove likely fraudulent responders, we included 77 participants in all analyses. Presurvey Likert scale responses indicated at least some comfort in using DLD terminology. Additionally, presurvey results of true/false DLD knowledge questions revealed high variability in respondents' knowledge of DLD. A McNemar chi-square test indicated statistically significant changes in participants' comfort levels in using DLD terminology from pre- to postsurvey for each question. A paired
t
test indicated statistically significant changes in DLD knowledge from pre- to postsurvey.

Conclusion:
Despite some limitations, it was concluded that diffusion efforts, such as educational presentations, are likely to increase SLPs' comfort levels in using DLD terminology and SLPs' knowledge of DLD.

Supplemental Material:

https://doi.org/10.23641/asha.22344349
Investigation into the linguistic category membership of the Finnish planning particletota
Authors: Kirjavainen Minna , Nikolaev Alexandre 
Published: April 2023

AbstractEven though hesitations (e.g.,um/uh) were historically perceived as involuntary non-linguistic items (e.g.,Maclay & Osgood 1959), more recently, a number of scholars have suggested that hesitations can behave like (a) lexical items (e.g.,Clark & Fox Tree 2002), and (b) at least in some contexts and with some functions as grammatical items like suffixes/clitics (Kirjavainen, Crible & Beeching 2022;Tottie 2017). The current study contributes to this body of work and presents two spoken language corpus analyses (frequency analysis; network analysis) investigating the nature of the Finnish planning particletota.Our results suggest thattotais more similar to grammatical items than lexical items.
Metaphorical framing in news
Authors: Saneie Moghadam Maryam , Ghafar Samar Reza 
Published: April 2023

Abstract
This study investigates metaphorical framing in political language. In particular, we describe dominant metaphoric frames which are used by the conservative and liberal media in the US when debating over the different aspects of the socio-political issues. The data for this study have been collected from the online archives of CNN and Fox news that were published on the two topics of medical healthcare system and immigration. We draw upon the ideas from some of the most recent semi-automated metaphor identification approaches to identify metaphors in texts. The findings of this study indicate that the US conservatives use a wider range of metaphorical frames to discuss the political issues. Some metaphorical frames are often used by both parties, while some others mark the divisive partisan rhetoric. Besides, the findings show that there are some metaphoric frames that are exclusively used to talk about a particular aspect of a topic.
Towards effective actions for the continuum limit of spin foams
Authors: Borissova Johanna N , Dittrich Bianca 
Published: April 2023

AbstractSpin foams arise from a quantization of classical gravity expressed via the Plebanski action. Key open questions related to the continuum limit of spin foams are whether general relativity is reproduced and what type of corrections could emerge. As a central component for spin foam dynamics, recent results on the continuum limit of the Area Regge action suggest a close relation with actions for area metrics instead of a length metric. Inspired by these results, within the framework of modified Plebanski theory we construct a family of candidate actions for area metrics. These actions are expected to describe the continuum limit of spin foams and provide a starting point to explore phenomenological aspects of the large-scale dynamics of spin foams. More generally, they set the stage for exploring consequences of an enlargement of the configuration space for gravity from length to area metrics. The actions we construct lead to an effective action for the length metric, describing a non-local and ghost-free version of Einstein–Weyl gravity.
Alleviating the cosmological constant problem from particle production
Authors: Belfiglio Alessio , Giambò Roberto , Luongo Orlando 
Published: April 2023

AbstractWe explore a toy model mechanism of geometric cancellation, alleviating the (classical) cosmological constant problem. To do so, we assume at primordial times that vacuum energy fuels an inflationary quadratic hilltop potential nonminimally coupled to gravity through a standard Yukawa-like interacting term, whose background lies on a perturbed Friedmann–Robertson–Walker metric. We demonstrate how vacuum energy release transforms into geometric particles, adopting a quasi-de Sitter phase where we compute the expected particle density and mass ranges. Perturbations are introduced by means of the usual external-field approximation, so that the back-reaction of the created particles on the geometry is not considered here. We discuss the limitations of this approach and we also suggest possible refinements. We then propose the most suitable dark matter candidates, showing under which circumstances we can interpret dark matter as constituted by geometric quasiparticles. We confront our predictions with quantum particle production and constraints made using a Higgs portal. In addition, the role of the bare cosmological constant is reinterpreted to speed up the Universe today. Thus, consequences on the standard ΛCDM paradigm are critically highlighted, showing how both coincidence and fine-tuning issues can be healed requiring the Israel–Darmois matching conditions between our involved inhomogeneous and homogeneous phases.
Design and test of the actuation circuit of the inertial sensor for space gravitational wave detection based on hardware-in-the-loop simulation
Authors: Zhang Qianyun , Liu Meilin , Wu Shufan 
Published: April 2023

Abstract
The key scientific performance of the inertial sensor used for space gravitational wave detection is the residual acceleration noise of the test mass (TM), which is caused by the noise of inertial sensor components and external environmental noise. As the actuator of the inertial sensor, the performance of the actuator circuit affects the residual acceleration noise, but it is difficult to test the residual acceleration noise with a single actuation circuit. In this study, the actuator circuit is designed and a low-cost hardware-in-the-loop simulation system combined actuation circuit and other parts of the inertial sensor are established to test the residual acceleration noise. The system is composed of simulator electronics and software simulator, which establishes the connection between the actuation circuit with the Simulink model. The displacement sensing, probe, and drag-free model were built in Simulink to form a closed loop with the actuation circuit through the serial port. The simulation and test results show that the hardware-in-the-loop simulation system can preliminarily test the residual acceleration of TM, and the residual acceleration introduced by the actuation circuit is 2.5 × 10−13 m s−2 Hz−1/2. Compared with the conventional test method, the system has the advantages of low cost, simple implementation, and easy extension to test any single inertial sensor module.
Valley-polarized and enhanced transmission in graphene with a smooth strain profile
Authors: Wang Sake , Tian Hongyu , Sun Minglei 
Published: April 2023

Abstract
We explore the influence of strain on the valley-polarized transmission of graphene by employing the wave-function matching and the non-equilibrium Green’s function technique. When the transmission is along the armchair direction, we show that the valley polarization and transmission can be improved by increasing the width of the strained region and increasing (decreasing) the extensional strain in the armchair (zigzag) direction. It is noted that the shear strain does not affect transmission and valley polarization. Furthermore, when we consider the smooth strain barrier, the valley-polarized transmission can be enhanced by increasing the smoothness of the strain barrier. We hope that our finding can shed new light on constructing graphene-based valleytronic and quantum computing devices by solely employing strain.
Invariant manifold growth formula in cylindrical coordinates and its application for magnetically confined fusion
Authors: Wei Wenyin , Liang Yunfeng 
Published: April 2023

Abstract
For three-dimensional vector fields, the governing formula of invariant manifolds grown from a hyperbolic cycle is given in cylindrical coordinates. The initial growth directions depend on the Jacobians of Poincaré map on that cycle, for which an evolution formula is deduced to reveal the relationship among Jacobians of different Poincaré sections. The evolution formula also applies to cycles in arbitrary finite n-dimensional autonomous continuous-time dynamical systems. Non-Möbiusian/Möbiusian saddle cycles and a dummy X-cycle are constructed analytically as demonstration. A real-world numeric example of analyzing a magnetic field timeslice on EAST is presented.