bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of uranium-235 distribution in soil samples from Anbar province, Western Iraq
Authors: Al-Ani Dunia Fadhil , Ahmed Rasha Sabeeh , Khalaf Hyam Nazmy Badr , Mostafa Mostafa Yuness Abdelfatah 
Published: October 2023

Abstract
Uranium is a radioactive element that can pose a risk to human health if ingested or inhaled. Exposure to high levels of uranium can increase the risk of cancer. Measuring uranium concentration in soil can help identify areas where there may be a risk of exposure to high levels of uranium and take appropriate measures to protect public health. In this study, uranium concentration in soil samples collected from Anbar province in Iraq was measured using CR-39 detectors irradiated with an Am-Be neutron source. The results showed that the highest concentration of uranium-specific activity (12.029 ± 0.0016 Bq kg−1) was found in Al Fallujah district, while the lowest concentration (0.531 ± 0.0007 Bq kg−1) was found in Al Sagra district. Interestingly, the data suggest that uranium concentrations increase as we move southeast towards Baghdad, where the city’s climate is reportedly polluted. Despite this, the average uranium-specific activity level in Anbar (7.668 Bq kg−1) is relatively low, and it falls below the global average of 35 Bq kg−1 recommended by the United Nations Scientific Committee on the Effects of Atomic Radiation. This study concludes that there is no evidence of uranium pollution in Anbar. Although uranium concentrations are considered low, low levels of uranium concentration in soil can have important implications for environmental risk, resource exploration, agricultural productivity, and geological research.
Best-case scenarios for neutrino capture experiments
Authors: Bondarenko Kyrylo , Boyarsky Alexey , Pradler Josef , Sokolenko Anastasia 
Published: October 2023

AbstractA direct discovery of the cosmic neutrino background would bring to a closure the searches for relic left-over radiation predicted by the Hot Big Bang cosmology. Recently, the KATRIN experiment put a limit on the local relic neutrino overdensity with respect to the cosmological predicted average value atη≲ 1011[Phys. Rev. Lett.129(2022) 011806]. In this work, we first examine to what extent such values ofηare conceivable. We show that even under cavalier assumptions, a cosmic origin ofη≳ 104seems out of reach (with the caveat of forming bound objects under a new force,) but find that a hypothetical local source of low-energy neutrinos could achieveη∼ 1011. Second, when such values are considered, we point out that the experimental signature in KATRIN and other neutrino-capture experiments changes, contrary to what has hitherto been assumed. Our results are model-independent and maximally accommodating as they only assume the Pauli exclusion principle. As intermittent physics target in the quest for CνB detection, we identify an experimental sensitivity toη∼ 104for which conceivable sources exist; to resolve the effect of a degenerate Fermi gas for such overdensity an energy resolution of 10 meV is required.
Simulation study of the influence of E× B drift on tungsten impurity transport in the scrape-off layer
Authors: Guo Jin , Xu Yuchen , Mao Shifeng , Ye Minyou 
Published: October 2023

Abstract
Tungsten (W) is used as the plasma-facing material in the divertor region of future fusion reactors, such as ITER; however, its concentration in the core plasma must be maintained at an extremely low level. W transport in the scrape-off layer (SOL), which is related to the source of core W contamination, has been extensively studied. In this study, the influence of E× B drift on the transport of W impurity in the SOL is studied via numerical simulations of a model case based on EAST upper single-null configuration with high recycling divertor plasma. W transport is simulated using DIVIMP on the background plasma obtained from scape-off layer plasma simulation-ITER simulation including drifts. The E× B drift of W ions is introduced based on the background electric field. Therefore, both the direct E× B drift effect of W ion and the indirect effect via background plasma on W transport in the SOL are studied. The influence on the flux of W impurities entering confined plasma across the last closed flux surface Γ
enter is focused on, which is expected to be proportional to the core W concentration. Results reveal that Γ
enter is mainly from the outer (inner) target under a favorable (unfavorable) toroidal field B
T and can be increased by more than one order of magnitude compared with the case without drifts; this reflects the significant effect of E× B drift. The effects due to the background plasma and the poloidal and radial E× B drift of W ion, as well as the related mechanisms, are analyzed in detail for three stages of W transport in the SOL: effective sputtering from the target, leakage from the divertor, and entry into the confined plasma.
Active particle in a harmonic trap driven by a resetting noise: an approach via Kesten variables
Authors: Guéneau Mathis , Majumdar Satya N , Schehr Grégory 
Published: October 2023

Abstract
We consider the statics and dynamics of a single particle trapped in a one-dimensional harmonic potential, and subjected to a driving noise with memory, that is represented by a resetting stochastic process. The finite memory of this driving noise makes the dynamics of this particle ‘active’. At some chosen times (deterministic or random), the noise is reset to an arbitrary position and restarts its motion. We focus on two resetting protocols: periodic resetting, where the period is deterministic, and Poissonian resetting, where times between resets are exponentially distributed with a rate r. Between the different resetting epochs, we can express recursively the position of the particle. The random relation obtained takes a simple Kesten form that can be used to derive an integral equation for the stationary distribution of the position. We provide a detailed analysis of the distribution when the noise is a resetting Brownian motion (rBM). In this particular instance, we also derive a renewal equation for the full time dependent distribution of the position that we extensively study. These methods are quite general and can be used to study any process harmonically trapped when the noise is reset at random times.
The association between air pollutants and depression in children and adolescents: a systematic review
Authors: Lian Xinyao , Wan Xiaoyu , Si Feifei , Guo Jianhui , Tang Ziqi , Wang Yaqi , Xie Shaodong , Li Jing 
Published: October 2023

Abstract
Depression is a common disease with a high prevalence among children and adolescents. Emerging evidence suggests that air pollution can increase the risk of depression. However, studies examining the relationship between air pollution and depression in children and adolescents are still in their nascent stages. We conducted a systematic review of current studies to investigate how air pollution and air quality issues relating to wildfires affect depression in children and adolescents aged 6 to 19. Our study found that both wildfire-related air exposure and air pollution may be associated with an increased risk of depression among children and teenagers. Ozone exerts a short-term impact on depression in young populations, whereas fine particulate matter (PM2.5) and NO2 have a long-term impact. Heterogeneity exists across studies, necessitating further investigation. Attention should be paid to the effects of air pollution and wildfires on the mental health of children and adolescents.
Bayesian renormalization
Authors: Berman David S , Klinger Marc S , Stapleton Alexander G 
Published: October 2023

Abstract
In this note we present a fully information theoretic approach to renormalization inspired by Bayesian statistical inference, which we refer to as Bayesian renormalization. The main insight of Bayesian renormalization is that the Fisher metric defines a correlation length that plays the role of an emergent renormalization group (RG) scale quantifying the distinguishability between nearby points in the space of probability distributions. This RG scale can be interpreted as a proxy for the maximum number of unique observations that can be made about a given system during a statistical inference experiment. The role of the Bayesian renormalization scheme is subsequently to prepare an effective model for a given system up to a precision which is bounded by the aforementioned scale. In applications of Bayesian renormalization to physical systems, the emergent information theoretic scale is naturally identified with the maximum energy that can be probed by current experimental apparatus, and thus Bayesian renormalization coincides with ordinary renormalization. However, Bayesian renormalization is sufficiently general to apply even in circumstances in which an immediate physical scale is absent, and thus provides an ideal approach to renormalization in data science contexts. To this end, we provide insight into how the Bayesian renormalization scheme relates to existing methods for data compression and data generation such as the information bottleneck and the diffusion learning paradigm. We conclude by designing an explicit form of Bayesian renormalization inspired by Wilson’s momentum shell renormalization scheme in quantum field theory. We apply this Bayesian renormalization scheme to a simple neural network and verify the sense in which it organizes the parameters of the model according to a hierarchy of information theoretic importance.
SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment
Authors: Tang Ziyang , Liu Xiang , Li Zuotian , Zhang Tonglin , Yang Baijian , Su Jing , Song Qianqian 
Published: October 2023

Abstract
Spatial cellular authors heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx, MERSCOPE and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels and transcriptomics coverage. Further application of SpaRx to the state-of-the-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance and identifies personalized drug targets and effective drug combinations.
Comparative study of the mechanism of natural compounds with similar structures using docking and transcriptome data for improvingin silicoherbal medicine experimentations
Authors: Park Musun , Baek Su-Jin , Park Sang-Min , Yi Jin-Mu , Cha Seongwon 
Published: October 2023

AbstractNatural products have successfully treated several diseases using a multi-component, multi-target mechanism. However, a precise mechanism of action (MOA) has not been identified. Systems pharmacology methods have been used to overcome these challenges. However, there is a limitation as those similar mechanisms of similar components cannot be identified. In this study, comparisons of physicochemical descriptors, molecular docking analysis and RNA-seq analysis were performed to compare the MOA of similar compounds and to confirm the changes observed when similar compounds were mixed and used. Various analyses have confirmed that compounds with similar structures share similar MOA. We propose an advanced method for in silico experiments in herbal medicine research based on the results. Our study has three novel findings. First, an advanced network pharmacology research method was suggested by partially presenting a solution to the difficulty in identifying multi-component mechanisms. Second, a new natural product analysis method was proposed using large-scale molecular docking analysis. Finally, various biological data and analysis methods were used, such as in silico system pharmacology, docking analysis and drug response RNA-seq. The results of this study are meaningful in that they suggest an analysis strategy that can improve existing systems pharmacology research analysis methods by showing that natural product–derived compounds with the same scaffold have the same mechanism.
DeepPeptide predicts cleaved peptides in proteins using conditional random fields
Authors: Teufel Felix , Refsgaard Jan Christian , Madsen Christian Toft , Stahlhut Carsten , Grønborg Mads , Winther Ole , Madsen Dennis 
Published: October 2023

Abstract

Motivation
Peptides are ubiquitous throughout life and involved in a wide range of biological processes, ranging from neural signaling in higher organisms to antimicrobial peptides in bacteria. Many peptides are generated post-translationally by cleavage of precursor proteins and can thus not be detected directly from genomics data, as the specificities of the responsible proteases are often not completely understood.

Results
We present DeepPeptide, a deep learning model that predicts cleaved peptides directly from the amino acid sequence. DeepPeptide shows both improved precision and recall for peptide detection compared to previous methodology. We show that the model is capable of identifying peptides in underannotated proteomes.

Availability and implementation
DeepPeptide is available online at ku.biolib.com/DeepPeptide.
What are a source and a sink under ecological and evolutionary perspectives?
Authors: Novaes Marisa de O , Bertassoni Alessandra , De Marco Júnior Paulo 
Published: October 2023

Abstract
Source–sink dynamics investigates species dispersal, mainly at the landscape scale, providing outcomes for conservation problem-solving. Designing conservation plans requires accurately identifying a source or a sink habitat within the landscape. However, this practical use demands a theoretical background and a clear definition of source and sink for its successful implementation. This study investigates the application of the terms source and sink, examining how biological features affect their use, and if they have been consistently applied in published studies. We conducted a systematic review focused on source–sink dynamics and performed descriptive and textual analysis to understand their application. Most research did not expressly state what a source or sink was, leaving a knowledge gap that prevents complete understanding and practical application. The concept of source has different uses and is better detailed than the term sink. The application of source and sink concepts was taxon-dependent; animal requirements are needed to indicate if a population/habitat can play a role as a source or sink. Because these concepts were being used differently, the source–sink terminology hinders fundamental theory, evolutionary perspectives, and applicability for species research and conservation, especially in the tropics, where a significant information gap was found.
Ovarian follicle size or growth rate can both be determinants of ovulatory follicle selection in mice
Authors: Richard Sharon , Zhou Yiran , Jasoni Christine L , Pankhurst Michael W 
Published: October 2023

Abstract
The endocrinology regulating ovulation of the desired number of oocytes in the ovarian cycle is well described, particularly in mono-ovulatory species. Less is known about the characteristics that make one follicle suitable for ovulation while most other follicles die by atresia. Bromodeoxyuridine (BrdU) injection was used to characterize granulosa cell proliferation rates in developing ovarian follicles in the estrous cycle of mice. This methodology allowed identification of follicle diameters of secondary (80–130 μm), follicle-stimulating hormone (FSH)-sensitive (130–170 μm), FSH-dependent (170–350 μm), and preovulatory (&gt;350 μm) follicles. Few preovulatory-sized follicles were present in the ovaries of mice at estrus, the beginning of the cycle. Progressive increases were seen at metestrus and diestrus, when full accumulation of the preovulatory cohort (~10 follicles) occurred. BrdU pulse-chase studies determined granulosa cell proliferation rates in the 24–48 h before the follicle reached the preovulatory stage. This showed that slow-growing follicles were not able to survive to the preovulatory stage. Mathematical modeling of follicle growth rates determined that the largest follicles at the beginning of the cycle had the greatest chance of becoming preovulatory. However, smaller follicles could enter the preovulatory follicle pool if low numbers of large antral follicles were present at the beginning of the cycle. In this instance, rapidly growing follicles had a clear selection advantage. The developing follicle pool displays heterogeneity in granulosa cell proliferation rates, even among follicles at the same stage of development. This parameter appears to influence whether a follicle can ovulate or become atretic.
The effects of short-term and long-term phthalate exposures on ovarian follicle growth dynamics and hormone levels in female mice
Authors: Santacruz-Márquez Ramsés , Safar Adira M , Laws Mary J , Meling Daryl D , Liu Zhenghui , Kumar T Rajendra , Nowak Romana A , Raetzman Lori T , Flaws Jodi A 
Published: October 2023

Abstract
Di(2-ethylhexyl) phthalate and diisononyl phthalate are widely used as plasticizers in polyvinyl chloride products. Short-term exposures to phthalates affect hormone levels, ovarian follicle populations, and ovarian gene expression. However, limited data exist regarding the effects of long-term exposure to phthalates on reproductive functions. Thus, this study tested the hypothesis that short-term and long-term exposure to di(2-ethylhexyl) phthalate or diisononyl phthalate disrupts follicle dynamics, ovarian and pituitary gene expression, and hormone levels in female mice. Adult CD-1 female mice were exposed to vehicle, di(2-ethylhexyl) phthalate, or diisononyl phthalate (0.15 ppm, 1.5 ppm, or 1500 ppm) via the chow for 1 or 6 months. Short-term exposure to di(2-ethylhexyl) phthalate (0.15 ppm) and diisononyl phthalate (1.5 ppm) decreased serum follicle-stimulating hormone levels compared to control. Long-term exposure to di(2-ethylhexyl) phthalate and diisononyl phthalate (1500 ppm) increased the percentage of primordial follicles and decreased the percentages of preantral and antral follicles compared to control. Both phthalates increased follicle-stimulating hormone levels (di(2-ethylhexyl) phthalate at 1500 ppm; diisononyl phthalate at 1.5 ppm) and decreased luteinizing hormone levels (di(2-ethylhexyl) phthalate at 0.15 and 1.5 ppm; diisononyl phthalate at 1.5 ppm and 1500 ppm) compared to control. Furthermore, both phthalates altered the expression of pituitary gonadotropin subunit genes (Cga, Fshb, and Lhb) and a transcription factor (Nr5a1) that regulates gonadotropin synthesis. These data indicate that long-term exposure to di(2-ethylhexyl) phthalate and diisononyl phthalate alters follicle growth dynamics in the ovary and the expression of gonadotropin subunit genes in the pituitary and consequently luteinizing hormone and follicle-stimulating hormone synthesis.
The clinical use of stress echocardiography in chronic coronary syndromes and beyond coronary artery disease: a clinical consensus statement from the European Association of Cardiovascular Imaging of the ESC
Authors: Picano Eugenio , Pierard Luc , Peteiro Jesus , Djordjevic-Dikic Ana , Sade Leyla Elif , Cortigiani Lauro , Van De Heyning Caroline M , Celutkiene Jelena , Gaibazzi Nicola , Ciampi Quirino , Senior Roxy , Neskovic Aleksandar N , Henein Michael 
Published: October 2023

Abstract
Since the 2009 publication of the stress echocardiography expert consensus of the European Association of Echocardiography, and after the 2016 advice of the American Society of Echocardiography-European Association of Cardiovascular Imaging for applications beyond coronary artery disease, new information has become available regarding stress echo. Until recently, the assessment of regional wall motion abnormality was the only universally practiced step of stress echo. In the state-of-the-art ABCDE protocol, regional wall motion abnormality remains the main step A, but at the same time, regional perfusion using ultrasound-contrast agents may be assessed. Diastolic function and pulmonary B-lines are assessed in step B; left ventricular contractile and preload reserve with volumetric echocardiography in step C; Doppler-based coronary flow velocity reserve in the left anterior descending coronary artery in step D; and ECG-based heart rate reserve in non-imaging step E. These five biomarkers converge, conceptually and methodologically, in the ABCDE protocol allowing comprehensive risk stratification of the vulnerable patient with chronic coronary syndromes. The present document summarizes current practice guidelines recommendations and training requirements and harmonizes the clinical guidelines of the European Society of Cardiology in many diverse cardiac conditions, from chronic coronary syndromes to valvular heart disease. The continuous refinement of imaging technology and the diffusion of ultrasound-contrast agents improve image quality, feasibility, and reader accuracy in assessing wall motion and perfusion, left ventricular volumes, and coronary flow velocity. Carotid imaging detects pre-obstructive atherosclerosis and improves risk prediction similarly to coronary atherosclerosis. The revolutionary impact of artificial intelligence on echocardiographic image acquisition and analysis makes stress echo more operator-independent and objective. Stress echo has unique features of low cost, versatility, and universal availability. It does not need ionizing radiation exposure and has near-zero carbon dioxide emissions. Stress echo is a convenient and sustainable choice for functional testing within and beyond coronary artery disease.