bluuebunny/crossref_metadata_2025 huggingface dataset:
Contrastive learning via swapped cluster assignments for bearing fault diagnosis
Authors: Wang Kai , Liu Chun , Chen Hongtian , Xiu Xianchao
Published: October 2023

In industrial scenarios, machinery and equipment operate in environments with many uncontrollable factors. These factors have a significant impact on vibration signals. For instance, differences in rotational speeds can make the collected data inconsistent. As a result, the tags collected from industrial environments are untrustworthy. It is impossible to know how many types of vibration signals are included in the dataset. In this paper, we propose a self-supervised pre-training method for bearing fault diagnosis called contrastive learning via swapped cluster assignments (CLSCA). Technically, CLSCA is based on momentum contrast (MoCo) and uses an unsupervised clustering algorithm to replace the classification of positive and negative samples in MoCo. By autonomously extracting representations from unlabelled datasets and then generating pseudo-labels using a clustering algorithm, CLSCA is able to learn in a self-supervised manner. When the value of the clustering center is in the appropriate range, the classification accuracy of CLSCA is improved by about

4
%

compared to MoCo.
Cross-medium imaging model and calibration method based on refractive optical path for underwater morphology measurement
Authors: Ding Tianhao , Sun Chen , Chen Jubing
Published: October 2023

Full-field optical morphology measurement methods are widely used in the shape measurement of underwater targets. The existing models and calibration methods in air could be invalid due to the refraction of light. To deal with these problems, this paper develops a cross-medium imaging model and a relative calibration method. In the modeling, the actual refraction optical path is considered when using arbitrary transparent structures. In the calibration, the accurate parameters of the model are first determined in the air environment and then updated by the refraction index replacement strategy. By using these methods, the accurate restoration of the morphology of objects in any medium is realized, and the inconvenience of underwater calibration process in prior methods can be avoided. The results of conducted experiments show that the accuracy of measurement can achieve 0.42%, which illustrates the validity of the proposed model and the precision of the proposed calibration method.
A method for compensating random errors in MEMS gyroscopes based on interval empirical mode decomposition and ARMA
Authors: Zeng Xin , Xian Sujie , Liu Kun , Yu Zhuolin , Wu Zhilin
Published: October 2023

The random error in micro-electro-mechanical systems (MEMS) gyroscopes is one of the major aspects that limit measurement accuracy. In order to address the inaccurate extraction of noise and trend during the signal preprocessing, as well as the subjectivity in autoregressive moving average (ARMA) model ordering, this paper proposes a method based on interval empirical mode decomposition and ARMA model. In the proposed method, the original signal is decomposed into a series of intrinsic mode functions (IMFs) and a residual through empirical mode decomposition (EMD). Based on the Hellinger distance and autocorrelation function, IMFs are then classified into noise IMFs, hybrid IMFs, and signal IMFs. The improved sand cat swarm optimization is utilized to optimize the ordering process of the ARMA model. The improved adaptive filter is adopted to compensate the random error, and the compensated signal is reconstructed with the signal IMFs and residual to obtain the final output. Experiments show that under static conditions, the proposed method could reduce the root mean square error (RMSE) by 52.6% and 33.3%, respectively, compared with the traditional EMD and ARMA methods. Under dynamic conditions, the proposed method could reduce the RMSE by 51.1% and 37.1%, respectively, compared with the traditional EMD and ARMA methods. The proposed method could effectively compensate the random error and improve the measurement accuracy of MEMS gyroscopes.
Conventional and pulsed hybrid triboelectric nanogenerator with tunable output time and wider impedance matching range
Authors: Shang Wanyu , Gu Guangqin , Ruan Haoran , Gu Guangxiang , Zhang Wenhe , Zhang Zhihao , Cheng Gang , Du Zuliang
Published: October 2023

Sliding grating-structured triboelectric nanogenerators (SG-TENGs) can multiply transferred charge, reduce open-circuit voltage, and increase short-circuit current, which have wide application prospects in self-powered systems. However, conventional SG-TENGs have an ultrahigh internal equivalent impedance, which reduces the output voltage and energy under low load resistances (<10 MΩ). The Pulsed SG-TENGs can reduce the equivalent impedance to near zero by introducing a synchronously triggered mechanical switch (STMS), but its limited output time causes the incomplete charge transfer under high load resistances (>1 GΩ). In this paper, a conventional and pulsed hybrid SG-TENG (CPH-SG-TENG) is developed through rational designing STMS with tunable width and output time. The matching relationship among grid electrode width, contactor width of STMS, sliding speed, and load resistance has been studied, which provides a feasible solution for simultaneous realization of high output energy under small load resistances and high output voltage under high load resistances. The impedance matching range is extended from zero to at least 10 GΩ. The output performance of CPH-SG-TENG under low and high load resistances are demonstrated by passive power management circuit and arc discharge, respectively. The general strategy using tunable STMS combines the advantages of conventional and pulsed TENGs, which has broad application prospects in the fields of TENGs and self-powered systems.
Structure, stability and electronic properties of zirconium nitride nanoclusters
Authors: Bhagowati Purbajyoti , Sahariah Munima B
Published: October 2023

Zirconium nitride (ZrN) is an industrial material having very high melting point, hardness and chemical stability. Compared to the bulk ZrN, its nanoclusters (NCs) are rarely explored. In this report, we generate a few ZrN NCs using ab initio molecular dynamics simulation. We investigate their electronic properties in terms of Bader charge, electron localization function and density of states. The obtained results are compared with their bulk counterpart. We also study the static and dynamical stability of the NCs with the help of binding energy, density of states and phonon dispersion spectra. The electron localization function of bulk ZrN is reported here for the first time to better understand its often confusing bonding behaviour.
Numerical investigation reveals challenges in measuring the contrast recovery coefficients in PET
Authors: Bayerlein Reimund , Spencer Benjamin A , Abdelhafez Yasser G , Cherry Simon R , Badawi Ramsey D , Omidvari Negar
Published: October 2023

Objective. Contrast recovery coefficient (CRC) is essential for image quality (IQ) assessment in positron emission tomography (PET), typically measured according to the National Electrical Manufacturers Association (NEMA) NU 2 standard. This study quantifies systematic uncertainties of the CRC measurement by a numerical investigation of the effects from scanner-independent parameters like voxel size, region-of-interest (ROI) misplacement, and sphere position on the underlying image grid. Approach. CRC measurements with 2D and 3D ROIs were performed on computer-generated images of a NEMA IQ-like phantom, using voxel sizes of 1–4 mm for sphere diameters of 5–40 mm—first in absence of noise and blurring, then with simulated spatial resolution and image noise with varying noise levels. The systematic uncertainties of the CRC measurement were quantified from above variations of scanner-independent parameters. Subsampled experimental images of a NEMA IQ phantom were additionally used to investigate the impact of ROI misplacement at different noise levels. Main results. In absence of noise and blurring, systematic uncertainties were up to 28.8% and 31.0% with 2D and 3D ROIs, respectively, for the 10 mm sphere, with the highest impact from ROI misplacement. In all cases, smaller spheres showed higher uncertainties with larger voxels. Contrary to prior assumptions, the use of 3D ROIs did not exhibit less susceptibility for parameter changes. Experimental and computer-generated images both demonstrated considerable variations on individual CRC measurements when background coefficient-of-variation exceeded 20%, despite negligible effects on mean CRC. Significance. This study underscores the effect of scanner-independent parameters on reliability, reproducibility, and comparability of CRC measurements. Our findings highlight the trade-off between the benefits of smaller voxel sizes and noise-induced CRC fluctuations, which is not considered in the current version of the NEMA IQ standards. The results furthermore warrant adjustments to the standard to accommodate the advances in sensitivity and spatial resolution of current-generation PET scanners.
MB-DECTNet: a model-based unrolling network for accurate 3D dual-energy CT reconstruction from clinically acquired helical scans
Authors: Ge Tao , Liao Rui , Medrano Maria , Politte David G , Williamson Jeffrey F , O’Sullivan Joseph A
Published: October 2023

Objective. Over the past several decades, dual-energy CT (DECT) imaging has seen significant advancements due to its ability to distinguish between materials. DECT statistical iterative reconstruction (SIR) has exhibited potential for noise reduction and enhanced accuracy. However, its slow convergence and substantial computational demands render the elapsed time for 3D DECT SIR often clinically unacceptable. The objective of this study is to accelerate 3D DECT SIR while maintaining subpercentage or near-subpercentage accuracy. Approach. We incorporate DECT SIR into a deep-learning model-based unrolling network for 3D DECT reconstruction (MB-DECTNet), which can be trained end-to-end. This deep learning-based approach is designed to learn shortcuts between initial conditions and the stationary points of iterative algorithms while preserving the unbiased estimation property of model-based algorithms. MB-DECTNet comprises multiple stacked update blocks, each containing a data consistency layer (DC) and a spatial mixer layer, with the DC layer functioning as a one-step update from any traditional iterative algorithm. Main results. The quantitative results indicate that our proposed MB-DECTNet surpasses both the traditional image-domain technique (MB-DECTNet reduces average bias by a factor of 10) and a pure deep learning method (MB-DECTNet reduces average bias by a factor of 8.8), offering the potential for accurate attenuation coefficient estimation, akin to traditional statistical algorithms, but with considerably reduced computational costs. This approach achieves 0.13% bias and 1.92% mean absolute error and reconstructs a full image of a head in less than 12 min. Additionally, we show that the MB-DECTNet output can serve as an initializer for DECT SIR, leading to further improvements in results. Significance. This study presents a model-based deep unrolling network for accurate 3D DECT reconstruction, achieving subpercentage error in estimating virtual monoenergetic images for a full head at 60 and 150 keV in 30 min, representing a 40-fold speedup compared to traditional approaches. These findings have significant implications for accelerating DECT SIR and making it more clinically feasible.
Image reconstruction from truncated fan-beam projections along a circular trajectory using the virtual fan-beam method
Authors: Charles Mathurin , Clackdoyle Rolf , Rit Simon
Published: October 2023

Objective. In this paper, we investigate how the virtual fan-beam (VFB) method can be used to perform mathematically correct 2D reconstruction in a region-of-interest (ROI), using truncated fan-beam projections acquired on a circular scan, for truncation that only occurs on one side of the object. Approach. We start by choosing a virtual fan-beam trajectory and specifying how to obtain the corresponding virtual projections. Then, three VFB formulas are obtained by applying known super-short-scan (SSS) formulas to this virtual trajectory. Two of them perform the backprojection in a virtual parallel geometry and the third in the virtual fan-beam geometry. Next, we develop two VFB formulas that perform the backprojection step in the fan-beam acquisition geometry. Main results. We present five VFB reconstruction formulas for this truncation setting. To our knowledge, the two VFB formulas performing the backprojection in the fan-beam acquisition geometry are new. Moreover, the five VFB formulas presented here obtain accurate reconstruction in a larger ROI than what has been previously reported in the literature in the same setting. A complete mathematical derivation of these five VFB formulas is given, and their implementation is described step by step. Numerical simulations, using the Forbild head and thorax phantoms, demonstrate the efficacy of these formulas. A spatial resolution analysis and a variance study indicate minor differences between these five VFB formulas. Significance. This work shows that many different VFB formulas can be applied to perform mathematically correct 2D reconstruction in a ROI, in case of truncated fan-beam projections acquired on a circular scan. Moreover, the two new VFB formulas, with backprojection in the acquisition geometry, may open the path for an extension of the VFB method to 3D reconstruction from transversely truncated cone-beam projection acquired on a circular scan.
Modelling intermittent anomalous diffusion with switching fractional Brownian motion
Authors: Balcerek Michał , Wyłomańska Agnieszka , Burnecki Krzysztof , Metzler Ralf , Krapf Diego
Published: October 2023

The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due to which the motion changes along the trajectories. Such effects manifest themselves as spatiotemporal correlations. Despite the broad occurrence of heterogeneous complex systems in nature, their analysis is still quite poorly understood and tools to model them are largely missing. We contribute to tackling this problem by employing an integral representation of Mandelbrot’s fractional Brownian motion that is compliant with varying motion parameters while maintaining long memory. Two types of switching fractional Brownian motion are analysed, with transitions arising from a Markovian stochastic process and scale-free intermittent processes. We obtain simple formulas for classical statistics of the processes, namely the mean squared displacement and the power spectral density. Further, a method to identify switching fractional Brownian motion based on the distribution of displacements is described. A validation of the model is given for experimental measurements of the motion of quantum dots in the cytoplasm of live mammalian cells that were obtained by single-particle tracking.
Discharge in electrospraying of highly conductive aqueous solution coated with outer ionic liquid
Authors: Cheng Yufeng , Wang Weizong , Yan Jiaqi , Wang Zhancheng
Published: October 2023

Discharge in electrospraying can be applied in water decontamination, dental sterilization, and spectrometry of biological samples. The discharge in electrospraying of a single liquid like the aqueous solution or the ionic liquid has been investigated, which presents different discharge characteristics such as patterns, currents and frequencies. This paper puts forward a way to actively control the discharge characteristics of liquids electrospray beyond the limitation of their own physical properties, which was accomplished by utilizing the technique of coaxial electrospray to coat the concentrated sodium chloride (NaCl) aqueous solution with a layer of ionic liquid. Previously we used this method to suppress the discharge of NaCl solution and stably electrosprayed the NaCl solution. The discharge characteristics of coaxial electrospray and the effect of the applied voltage and the flow rates of both liquids on the discharge was investigated in detail. When being electrosprayed, the NaCl solution alone discharged with pre-onset mode, pulseless corona discharge mode and streamer discharge mode, while the ionic liquid and the coaxial electrospray only discharged with the streamer discharge mode with a conical liquid shape, and less droplets were formed during the transient cone-jet emission. After being coated with the outer ionic liquid, the current, frequency and onset voltage of the discharge of the inner aqueous solution all increased. The current and frequency of the discharge of the coaxial electrospray all increased as the applied voltage increased. In addition, a numerical simulation has been conducted, which confirmed that the inner aqueous solution was strongly shielded from the external electric field by the outer ionic liquid layer. Therefore, it is plausible to actively control the discharge characteristics of the liquids through adjusting the flow rates of both liquids, the applied voltage and choosing the suitable outer liquid.
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

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

A 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

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

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

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

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.
Characterizations of a class of weighted 𝐵𝑀𝑂 spaces via commutators of intrinsic square functions
Authors: Han Yanyan , Wu Huoxiong
Published: October 2023

The intrinsic square functions including the Lusin area function, Littlewood-Paley

g
g

-function and

g
λ
∗

g^\ast _\lambda

-function dominate pointwisely the classical Littlewood-Paley functions and can be used to characterize the weighted Hardy spaces and more general Musielak-Orlicz Hardy spaces etc. This paper shows that for

b
∈

B
M
O
(

R

n

)

b\in \mathrm {BMO(\mathbb {R}^n)}

, the commutators generated by these intrinsic square functions with

b
b

are bounded from

H
ω
p

(

R

n

)

H^p_\omega (\mathbb {R}^n)

to

L
ω
p

(

R

n

)

L^p_\omega (\mathbb {R}^n)

for some

0
>
p
≤
1

0>p\le 1

and

ω
∈

A
∞

\omega \in A_\infty

if and only if

b
∈

B
M
O

ω
,
p

(

R

n

)

b\in \mathcal {BMO}_{\omega ,p}(\mathbb {R}^n)

, which are a class of non-trivial subspaces of

B
M
O
(

R

n

)

\mathrm {BMO(\mathbb {R}^n)}

.
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

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

Natural 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

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

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

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 (>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

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

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.
Dose dependence of prenatal fluoride exposure associations with cognitive performance at school age in three prospective studies
Authors: Grandjean Philippe , Meddis Alessandra , Nielsen Flemming , Beck Iben H , Bilenberg Niels , Goodman Carly V , Hu Howard , Till Christine , Budtz-Jørgensen Esben
Published: October 2023

Background

Fluoride may be a developmental neurotoxicant at elevated exposures. We merged new data from a prospective Odense Child Cohort (OCC) with results from two previous birth cohort studies from Mexico and Canada to characterize the dose–effect relationship in greater detail.

Methods

The OCC contributed 837 mother–child pairs to the total of >1500. We measured creatinine-adjusted urine-fluoride concentrations in maternal urine samples obtained during late pregnancy. Child IQ was determined at age 7 years using an abbreviated version of the Wechsler Intelligence Scales for Children. Findings from the three cohorts were used to calculate the joint benchmark concentration (BMC) and the lower confidence limit (BMCL) after adjustment for covariables.

Results

In the OCC, urine-fluoride concentrations varied between 0.08 and 3.04 mg/l (median 0.52 mg/l) but were not significantly associated with full-scale IQ at age 7 years (β = 0.08; 95% confidence interval −1.14 to 1.30 for a doubling in exposure). No difference was apparent between boys and girls. In the OCC, the BMC was 0.92 mg/l, with a BMCL of 0.30 mg/l. The joint analysis of all three cohorts showed a statistically significant association between urine-fluoride and IQ, with a BMC of 0.45 mg/l (BMCL, 0.28 mg/l), slightly higher than the BMC previously reported for the two North American cohorts alone.

Conclusions

As the BMCL reflects an approximate threshold for developmental neurotoxicity, the results suggest that pregnant women and children may need protection against fluoride toxicity.
Externalizing Behaviors and Alzheimer’s Disease and Any Dementia: A Multigeneration Cohort Study in Sweden
Authors: Solares Carmen , Zhang Le , Chang Zheng , Andershed Henrik , Persson Jonas , Larsson Henrik
Published: October 2023

Background and Objectives

We examined the extent to which externalizing behaviors such as violent and nonviolent criminal behavior, and substance use disorders (SUD) are associate with the onset of Alzheimer’s disease (AD) and any dementia in prior generations.

Research Design and Methods

A nationwide cohort of 2,463,033 individuals born between 1973 and 1997 (index persons) were linked to their biological relatives (parents, grandparents, and uncles/aunts) using Swedish national registers. Cox regression models were used to examine the association between each measure of externalizing behaviors with AD and any dementia in each of the relative cohorts.

Results

Parents of index persons with externalizing behaviors had an increased risk for AD compared with parents of index persons without externalizing behaviors—nonviolent criminal behavior: Hazard Ratio (HR) = 1.16, 95% Confidence Intervals (CI) 1.10–1.22; violent criminal behavior: HR = 1.32 (95% CI: 1.19–1.45); SUD: HR = 1.28 (95% CI: 1.17, 1.40). The associations attenuated with decreasing familial relatedness. Relatives of individuals with externalizing behaviors compared with relatives of individuals without, showed an increased risk of having both early-onset and late-onset AD but the strength of the associations was higher for early-onset AD than for late-onset AD. A similar pattern of results was observed for the association with any dementia.

Discussion and Implications

Externalizing behaviors are associated with AD and any dementia in prior generations. The associations were stronger for parents in comparison with grandparents and uncles/aunts, suggesting shared familial risks between conditions. This warrants further studies examining common genetic and family-wide environmental factors that may contribute to identifying common underlying mechanisms to the development of externalizing behaviors, AD, and any dementia.
Causal relationship between gastro-esophageal reflux disease and risk of lung cancer: insights from multivariable Mendelian randomization and mediation analysis
Authors: Liu Yi , Lai Hongjin , Zhang Ren , Xia Liang , Liu Lunxu
Published: October 2023

Aim

A recent study has reported that anti-reflux surgery reduced the risk of lung cancer. However, the exact causal association between gastro-esophageal reflux disease (GORD) and lung cancer remains obscure. Therefore, we conducted a multivariable and network Mendelian randomization (MR) study to explore this potential association and mediation effect.

Methods

Independent single nucleotide polymorphisms (SNPs) strongly associated with GORD were selected as instrumental variables (IVs) from the corresponding genome-wide association studies (GWAS). The summary statistics were obtained from the largest GORD GWAS meta-analysis of 367 441 (78 707 cases) European individuals, and the summary statistics of lung cancer and pathological subtypes came from International Lung Cancer Consortium (ILCCO) and FinnGen databases. Univariable and multivariable MR analyses were performed to investigate and verify the causal relationship between genetically predicted GORD and lung cancer. Network MR analysis was conducted to reveal the mediating role of GORD between smoking initiation and lung cancer.

Results

The univariable MR analysis demonstrated that GORD was associated with an increased risk of total lung cancer in both ILCCO [inverse variance weighted (IVW): odds ratio (OR) = 1.37, 95% confidence interval (CI) 1.16–1.62, P = 1.70E-04] and FinnGen database (IVW: OR = 1.25, 95% confidence interval CI 1.03–1.52, P = 2.27E-02). The consistent results were observed after adjusting the potential confounders [smoking traits, body mass index (BMI) and type 2 diabetes] in multivariable MR analyses. In subtype analyses, GORD was associated with lung adenocarcinoma (IVW: OR = 1.27, 95% CI 1.02–1.59, P = 3.48E-02) and lung squamous cell carcinomas (IVW: OR = 1.50, 95% CI 1.22–1.86, P = 1.52E-04). Moreover, GORD mediated 32.43% (95% CI 14.18–49.82%) and 25.00% (95% CI 3.13–50.00%) of the smoking initiation effects on lung cancer risk in the ILCCO and FinnGen databases, respectively.

Conclusion

This study provides credible evidence that genetically predicted GORD was significantly associated with an increased risk of total lung cancer, lung adenocarcinoma and lung squamous cell carcinomas. Furthermore, our results suggest GORD is involved in the mechanism of smoking initiation-induced lung cancer.