bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic noise characterisation at a potential gravitational wave detector site in Australia
Authors: Satari Hamid , Blair Carl , Ju Li , Blair David , Zhao Chunnong , Saygin Erdinc , Meyers Patrick , Lumley David
Published: April 2023

A critical consideration in the design of next-generation gravitational wave detectors is the understanding of the seismic environment that can introduce coherent and incoherent noise of seismic origin at different frequencies. We present detailed low-frequency ambient seismic noise characterisation (0.1–10 Hz) at the Gingin site in Western Australia. Unlike the microseism band (0.06–1 Hz) for which the power shows strong correlations with nearby buoy measurements in the Indian Ocean, the seismic spectrum above 1 Hz is a complex superposition of wind induced seismic noise and anthropogenic seismic noise which can be characterised using beamforming to distinguish between the effects of coherent and incoherent wind induced seismic noise combined with temporal variations in the spatio-spectral properties of seismic noise. This also helps characterise the anthropogenic seismic noise. We show that wind induced seismic noise can either increase or decrease the coherency of background seismic noise for wind speeds above 6 m s−1 due to the interaction of wind with various surface objects. In comparison to the seismic noise at the Virgo site, the secondary microseism (0.2 Hz) noise level is higher in Gingin, but the seismic noise level between 1 and 10 Hz is lower due to the sparse population and absence of nearby road traffic.
On causality conditions in de Sitter spacetime
Authors: Bittermann Noah , McLoughlin Daniel , Rosen Rachel A
Published: April 2023

We carefully consider the Shapiro time delay due to black holes and shockwaves in de Sitter spacetime and study the implications for causality. We discuss how causality conditions of AdS and flat spacetime can be applied in de Sitter spacetime, using spatial shifts measured on the boundary to define ‘fastest null geodesics’ and taking into account the ‘stretching’ of the de Sitter Penrose diagram. We consider the propagation of a massless spin-1 field with a non-minimal coupling in a de Sitter shockwave background as an illustrative example. We also briefly discuss connections to the average null energy condition.
On the dielectric properties of bisphenol A and F epoxy resins blends based on molecular dynamics
Authors: Wang Y F , Du B X , Kong X X , Li Fan , Lin Xin
Published: April 2023

Bisphenol A and F epoxy resins are often used as the primary insulation in power equipment. This paper investigates the influence of network structure on the dielectric properties of bisphenol A, bisphenol F epoxy resin and their blends. The results show that substituting isopropyl with methylene in epoxy resin enhances the molecular chain packing efficiency, thus limiting the polarization effect while reducing glass transition temperature (T
g). As the content of bisphenol F resin in the blends increases, the polarization loss of the blends continues to decrease, to even lower than that of bisphenol F resin. For the blend containing 20% bisphenol F resin, the T
g and AC breakdown strength at high temperatures are higher than that of bisphenol A resin. Furthermore, based on molecular dynamics simulation, the reason for the limited polarization effect of the blends is further discussed.
Excitation wavelength-dependent ultrafast THz emission from surface and bulk of three-dimensional topological insulators
Authors: Nivedan Anand , Kumar Sunil
Published: April 2023

Three-dimensional topological insulators possess various interesting properties that are promising for various modern applications, including in the recently emerging fields of ultrafast THz photonics and spintronics. Their gapless spin-momentum-locked topological surface states with the presence of chiral spin structure are relevant for the development of light helicity-sensitive THz emitters and detectors. In this paper, we report femtosecond excitation pulse wavelength and helicity-dependent response of Bi2Te3 and Bi2Se3 for an enhanced broadband THz pulse emission from the surface and bulk states. Specifically, the excitation wavelength has been varied in a large range from near UV to near IR, where it was observed that the photoexcitation at shorter wavelengths enhances the THz emission from both the surface and bulk states but more rapidly from the surface states. These results will be highly relevant for developing chirality-sensitive efficient THz emitters and detectors.
High sensitivity mercury ion fiber optic sensor based on Mach–Zehnder interference
Authors: Jin Xuemei , Pan Dongmei , Pan Jingshun , Huang Xuguang
Published: April 2023

This paper proposes a novel optical fiber sensor for highly sensitive Hg2+ detection based on Mach–Zehnder interference (MZI) structure and thiophene–chitosan hydrogel (TCH). We obtained the MZI structure by splicing the coreless fiber (CLF), thin core fiber, and CLF. And then, we etched the thin-core optical fiber cladding and assembled the TCH to produce a Hg2+ sensitive sensor. According to theoretical derivation and experimental verification, the detection sensitivity of the sensor to Hg2+ can reach 1.008 × 1011 mol l−1, and the detection limit is 5 × 10−13 mol l−1. The sensor also has performance stability within 24 h for concentration measurement, with an average standard deviation of 3.2 × 10−13 mol l−1 within an hour of observation. In addition, the sensor has the advantages of specificity, simple preparation, and low cost, and it is suitable for monitoring the concentration of Hg2+ in complex water systems.
Theoretical studies on optical properties of Beltrami-shaped curved graphene
Authors: Hasanirokh K , Naderi F , Mohammadpour H
Published: April 2023

We compute the optical conductivity and polarization for an out-of-plane deformation in graphene nanostructure using a theoretical approach based on Dirac equation solutions on curved

2
+
1

dimensional space-time, where the space part is considered to correspond to the Beltrami pseudosphere which belongs to the family of surfaces with negative constant Gaussian curvature. We found that different parameters of deformation along one direction translate into an enhancement of the optical conductivity peaks and polarization magnitude in the far-infrared frequencies. This allows for a very high degree of polarization with a single layer graphene and opens up a potential prospect of employing graphene layer as efficient polarizers. Therefore the experimental predictions related to the electronic configuration of the corresponding graphene-like sample may be explicitly worked out.
Multi-task neural network blind deconvolution and its application to bearing fault feature extraction
Authors: Liao Jing-Xiao , Dong Hang-Cheng , Luo Lei , Sun Jinwei , Zhang Shiping
Published: April 2023

Blind deconvolution (BD) is an effective method to extract fault-related characteristics from vibration signals. Previous researches focused on two primary approaches to improve the robustness and effectiveness of BD methods: developing new optimization functions or devising new methods for estimating filter coefficients. However, these methods often suffer from the difficulty of finding the global optimum due to the complex non-convex functions. To address this issue, we propose a novel multi-objective criterion, combining two well-established sparsity criteria: kurtosis and

G
−

l
1

/

l
2

norm, that evaluates signal characteristics in both the time and frequency domains. We observe that this criterion, consisting of two sparsity criteria with opposite monotonicity, can mutually constrain and avoid overfitting that occurs with single-domain optimization. Inspired by multi-task convolutional neural networks, we introduce a multi-task 1DCNN with two branches to optimize the criterion in both domains simultaneously. To our best knowledge, it is the first time a multi-task convolutional neural network is used for BD problems. Experiments show that our method outperforms other state-of-the-art BD methods. We have share our code in https://github.com/asdvfghg/MNNBD
An enhanced instantaneous angular speed estimation method by multi-harmonic time–frequency realignment for wind turbine gearbox fault diagnosis
Authors: Li Cheng , Wang Yi , Zhang Guangyao , Qin Yi , Tang Baoping
Published: April 2023

Gearboxes are one of the most critical transmission devices in wind turbines (WTs). Order tracking (OT) of variable-speed WT gear is a powerful means to carry out fault diagnosis. Since it is difficult to install a tachometer or encoder for gearboxes with limited structural space, it is impossible to obtain the instantaneous angular speed (IAS) of the gearbox. In recent years, many tacholess techniques have been presented to estimate instantaneous phase from vibration signals for OT. However, their performance needs to be further improved to get a more exact diagnosis result. To solve this issue, this paper presents an enhanced IAS estimation approach for WT tacholess order tracking (TLOT), which is available for accurate IAS estimation of the rotating shaft, so that TLOT can be more effectively conducted under conditions of large speed variation and background noise. An improved cost function algorithm is designed to extract the IAS from the vibration signal. A Vold–Kalman filter and Hilbert transform are combined to calculate the instantaneous phase. Afterwards, the raw non-stationary vibration signal is resampled at an equal angle increment, and the envelope order spectrum is calculated from the resampled signal for fault diagnosis of the WT gearbox. The main innovating idea of this approach is to improve the traditional cost function ridge-extraction method by introducing gradient information based on probability and multi-harmonic time–frequency realignment, which makes the IAS estimation process more accurate and overcomes the limitations of traditional IAS estimation techniques. The effectiveness of the presented approach is demonstrated by using a vibration signal measured from real-world WT gearboxes, and the validation results demonstrate that the presented approach surpasses some state-of-the-art methods in IAS estimation accuracy and efficiency.
2D analytical modelling of asymmetric junctionless dual material double gate MOSFET for biosensing applications considering steric hindrance issue
Authors: Basak Arighna , Deyasi Arpan , Sarkar Angsuman
Published: April 2023

The current manuscript for Asymmetric Junctionless Dual Material Double Gate MOSFET (AJDMDG MOSFET) biosensor reports improved sensitivity for both threshold voltage and ON-current. In the presence of high-K dielectric material, the device was built using both neutral and charged biomolecules. After calculating the minimal surface potential, the threshold voltage is calculated by solving the 2D Poisson’s equation using a parabolic-potential configuration under realistic boundary circumstances. Analytical results show good agreement with TCAD simulation, prompting an exploration of threshold voltage sensitivity with front-gate voltage changes of all possible dimensions. Corresponding drain current sensitivity with a higher ON-to-OFF current ratio is theoretically estimated and compared with identical DGFET architecture, resulting in a significant improvement for all possible step patterns when steric hinderance is considered for moderately filled cavities; this aids in detecting both labelled and label-free electrical species at lower concentration levels.
First principle study of electronic and optical properties of WS2(1-x)Se2x obtained by isoelectronic Se substitution on S-site of monolayer WS2
Authors: Saha Ajoy Kumar , Gupta Partha Sarathi , Rahaman Hafizur
Published: April 2023

Two-dimensional semiconducting transition metal dichalcogenides have recently grabbed attention among the researchers, due to their extraordinary electrical, optical and thermal properties. Also, they have shown their suitability for application in digital electronics, photovoltaic cells, Thermoelectric generators and so on. Still, it is desired to precisely control the material properties to expand their scope of application and revamp the device performance. The substitutional doping technique is one of the widely explored processes, which is conventionally used to modulate the material properties. In the present work, the substitutional doping of selenium at the sulfur site within the WS2 sheet, is used indigenously to improve the electrical and optical response of the material. In doing so, electrical and optical properties of such doped materials are studied by employing density functional theory and linearized Boltzmann transport equation by considering the relaxation time approximation. The study has shown an almost linear variation of electronic band gap energy with the doping percentages. Also, the electron and hole mobility were found to be tailored due to the doping. Notably, hole mobility has shown a noticeable improvement at or near 60 percent of selenium doping. In the last section of the current work, the optical properties are extracted for the doped structures. The WS2 monolayer has shown the highest absorption peak near 3 eV. But for the doped materials, absorption peaks are relatively smaller and left shifted in the energy axis due to their low band gap energies.
Probing axions via light circular polarization and event horizon telescope
Authors: Shakeri Soroush , Hajkarim Fazlollah
Published: April 2023

The impact of axion-like particles on the light polarization around the horizon of supermassive black hole (SMBH) is discussed in the light of the latest polarization measurement of the Event Horizon Telescope
(EHT). We investigate different sources of the polarization due to axion interaction with photons and the magnetic field of SMBH. These can modify the linear and circular polarization parameters of the emitted light. We have shown that a significant circular polarization can be produced via the photon scattering from the
background magnetic field with axions as off-shell particles. This can further constrain the parameter space of ultralight axion-like particles and their couplings with photons. The future precise measurements of circular
polarization can probe the features of ultralight axions in the near vicinity of SMBH.
Self-interacting gravitational atoms in the strong-gravity regime
Authors: Chia Horng Sheng , Doorman Christoffel , Wernersson Alexandra , Hinderer Tanja , Nissanke Samaya
Published: April 2023

We numerically investigate free and self-interacting ultralight scalar fields around black holes in General Relativity. We focus on complex scalar fields Φ whose self-interactions are described by the quartic potential V ∝ λ |Φ|4, and ignore the black hole spin in order to disentangle the effects of self interactions on the boson cloud. Using the spectral solver Kadath, we compute quasi-equilibrium configurations of the dominant eigenstates, including their backreaction on the spacetime metric. For scenarios with -10-2 ≲ λ ≲ 10-2 we find the mass of the self-interacting scalar cloud to be up to ∼ 70% larger than that of a free scalar cloud, though the additional backreaction effect on the spacetime metric is only up to ∼ 1% due to the low-density nature of the bosonic configurations. In this region of parameter space we observe approximate quadratic scalings between the mass of the cloud with λ, the scalar field amplitude, and the couplings between these two parameters. For systems with λ beyond this range, the eigenfrequencies differ sufficiently from the known free-test-field values used as inputs in our numerical setup
to make the results, though convergent, physically unreliable.
This bounds the range of λ in which the free scalar field solution remains a good approximation to self-interacting scalar field configurations. Our work is among the first nonperturbative explorations of self-interacting bosonic clouds around black holes, yielding detailed new insights into such systems in the nonlinear regime, while also overcoming technical challenges and quantifying limitations. Additionally, our results provide useful inputs
for fully dynamical numerical relativity simulations and for future explorations of spinning black holes and real scalar fields.
Search for stochastic gravitational-wave background from string cosmology with Advanced LIGO and Virgo's O1∼O3 data
Authors: Jiang Yang , Fan Xi-Long , Huang Qing-Guo
Published: April 2023

String cosmology models predict a relic background of gravitational-wave (GW) radiation in the early universe. The GW energy spectrum of radiated power increases rapidly with the frequency, and therefore it becomes a potential and meaningful observation object for high-frequency GW detector. We focus on the stochastic background generated by superinflation in string theory and search for such signal in the observing data of Advanced LIGO and Virgo O1∼O3 runs in a Bayesian framework. We do not find the existence of the signal, and thus put constraints on the GW energy density. Our results indicate that at f = 100 Hz, the fractional energy density of GW background is less than 1.7 × 1-8 and 2.1 × 10-8 for dilaton-string and dilaton only cases respectively, and further rule out the parameter space restricted by the model itself due to the non-decreasing dilaton and stable cosmology background (β bound).
Multiwavelength analysis of Galactic Supernova Remnants
Authors: Sharma P. , Ou Z. , Henry-Cadrot C. , Dubos C. , Suomijärvi T.
Published: April 2023

The origin of Galactic Cosmic Rays (CRs) and the possibility of Supernova Remnants (SNRs) being potential CR accelerators is still an open debate. The charged CRs can be detected indirectly by the γ-ray observatories through the π
0 production and consequent decay, leading to the generation of high-energy γ-rays. The goal of the study is to identify qualitative and quantitative trends in favour of hadronic scenario and search for SNRs which could be potential accelerators up to PeV energies (PeVatrons).

We have performed a Multiwavelength (MWL) study using different radiative models to evaluate the hadronic contribution. The spectral energy distributions (SEDs) of selected SNRs are modeled using the Naima [1] package. Two different radiative scenarios are considered, pure leptonic and lepto-hadronic scenarios and different methods are used to evaluate their importance.

This study shows that the lepto-hadronic scenario is favored for most SNRs. Two particular indicators of hadronic contribution come from the data around the π
0 production threshold and the data above a few TeV. The hard rise at the π
0 production threshold cannot be explained by leptonic processes. More data in this region would be valuable for these studies. For some SNRs, an important hadronic contribution is observed up to a few TeV, thus making them promising PeVatron candidates. In this high-energy region where the leptonic processes are expected to be suppressed, more data is required to help distinguish between the leptonic and hadronic origin of γ-ray emission. In the future, we intend to use the obtained model parameters to simulate data for CTA and assess its capability to identify PeVatrons.
Coherent control of the incident light propagation in a defect one-dimensional photonic crystal
Authors: Guo Zichao , Xiao Yuxin , Wang Yintao , Hou Huiyu
Published: April 2023

In this paper, we have discussed the transmission and reflection properties of the infrared laser pulse propagated through one-dimensional photonic crystal (1DPC) with single layer of graphene nanotrusses. The single layer graphene system interacts with a probe laser field and two coupling lights. We analytically solve the optical susceptibility of the single layer graphene system for adapting the dielectric function of the 1DPC. After that we discuss the transmission and reflection properties of the incident laser pulse on 1DPC by controlling the intensity for the coupling lights and relative phase between applied lights. We have also found that the absorption and population spectrums of the medium can be controlled by the relative phase between applied lights. Our results show that the gain without population inversion can be obtained for the simultaneous slow light propagation in the transmission and reflection pulses. Our results may have potential application in the future of the all-optical devices in quantum technologies.
Impacts of low-order aberrations on capacity of orbital-angular-momentum quantum states
Authors: Hu Zheng-Da , Wang Jicheng , Zhu Yun , Li Mengmeng , Khakhomov Sergei , Semchenko Igor
Published: April 2023

We use Hypergeometric Gaussian-II (HyGG-II) modes to investigate the impacts of non-Kolmogorov atmospheric turbulence on the Holevo channel capacity of a quantum communication scheme. The capacity of HyGG-II modes can be higher than that of Laguerre–Gaussian modes via modulating the hollowness parameter. The influences of low-order turbulence aberrations including tilt, defocus, astigmatism, and coma on the capacity are also explored. Generally, tilt aberration dominates among all low-order aberrations and defocus and astigmatism aberrations are always negligible. By contrast, the effect of coma aberration can be enhanced to be non-negligible when the turbulence strength or the channel zenith angle is enhanced. We also show that only the total and tilt aberrations are sensitive to the non-Kolmogorov power-law exponent. Our results may contribute to the quantum optical communication as well as aberration compensation in turbulent channels utilizing the novel family of vortex beams.
Characterizing the development and drivers of 2021 Western US drought
Authors: Affram Grace , Zhang Wei , Hipps Lawrence , Ratterman Cody
Published: April 2023

Understanding the drivers of the major 2021 drought conditions across the Western U.S. (WUS) is important to develop future resilience and adaptation measures. While evapotranspiration (ET) tends to increase in a warming climate when water is available, areas with low precipitation would evaporate less water than expected, as seen in the 2021 drought. This study examines the relative roles of higher temperatures and lower precipitation, as well as anthropogenic forcing (e.g. increased greenhouse gases and land-use land-cover change) to the 2021 drought across the WUS. Using observations, the anomalously dry 2021 soil moisture is mainly tied to precipitation deficit, rather than higher temperatures, suggesting that an increase in ET in response to higher temperatures (i.e. saturation deficit) depends on water availability. Therefore, high temperatures may play only a secondary role in driving the 2021 drought condition across the WUS. Additionally, a suite of variable infiltration capacity model experiments confirms that the reduced precipitation in 2021 has caused negative soil moisture anomalies. Based on the Coupled Model Intercomparison Project Phase 6 experiments, anthropogenic forcing dramatically increases the risk of the extreme 2021 dryness, with risk ratio being 73.91, 12.78 and 25.81 for temperature, precipitation, and soil moisture respectively. Therefore, the extreme drought is not explained by natural forcing (e.g. solar irradiance and volcanic eruption) alone. Rather, anthropogenic forcing (e.g. increased greenhouse gases and land-use land-cover change) has increased the risk of this drought condition by approximately 26 times in terms of soil moisture compared with a world without this forcing.
Quantum statistical mechanics of dissolving Abelian Higgs vortices
Authors: Manton N S , Wang Shiyi
Published: April 2023

The quantum partition function for Abelian Higgs vortices at high density—the regime of dissolving vortices—is calculated explicitly, using spectral data for the Beltrami Laplacian on the N-vortex moduli space

C
P

N

with a scaled Fubini–Study metric. From the partition function, the pressure of the vortex gas is derived. There are three asymptotic regimes—High, Intermediate and Low Temperature. The phase crossover from Intermediate to Low Temperature is modelled by a Bessel function. In the Low Temperature regime the free energy is not extensive but is proportional to N
2.
Variability modes of September Arctic sea ice: drivers and their contributions to sea ice trend and extremes
Authors: Karami Mehdi Pasha , Koenigk Torben , Tremblay Bruno
Published: April 2023

The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.
A practical guide to expert learner skills in the research environment
Authors: Duncan Mara C.
Published: April 2023

The ability to complete an experiment successfully without mistakes is at the core of the scientific enterprise. Some scientists seem more able to avoid mistakes and missteps than others. In the field of cell biology, their success is often attributed to having naturally good hands. Here I propose that rather than possessing “good hands,” an innate and unlearnable aptitude for science, such scientists possess expert learning skills that can be effectively mastered. I share a straightforward approach to gaining and teaching expert learning skills in the research lab environment. I also discuss ongoing efforts by others to develop curricula that teach expert learning skills in laboratory courses.
Introduction: ‘Killed by Idle Gossip’
Authors: Eidinow Esther
Published: April 2023

This chapter introduces an exploration of the context in which the trials of Theoris, Phryne, and Ninon took place.
‘Dangerous Women’
Authors: Eidinow Esther
Published: April 2023

This chapter takes its title from a phrase used by Michael Jameson to describe the women who were brought to court in ancient Athens in this period. This chapter builds on Jameson’s arguments, examining evidence from law-court speeches that suggests that there were widespread anxieties about women’s freedom and activities in fourth-century Athens—and the threat posed by them to the oikos (‘family’) and the polis. In contrast, inscribed epitaphs, which develop during the fourth century BCE, offer the idealized characteristics of a woman. This parallel discourse of public praise similarly focuses on the oikos. We see how on the one hand, a good woman or wife can support such a structure, while, on the other, her opposite can wholly undermine it, threatening family, city, state.
B-cell lineage neoplasms transdifferentiating into histiocytic/dendritic cell neoplasms: diversity, differentiation lineage, genomic alterations, and therapy: Report from the 2021 SH/EAHP Workshop
Authors: Xiao Wenbin , Amador Catalina , Cook James R , Czader Magdalena , Dave Sandeep , Dogan Ahmet , Duffield Amy , Goodlad John , Nejati Reza , Ott German , Wasik Mariusz
Published: April 2023

Objectives

To report findings from the 2021 Society for Hematopathology/European Association for Haematopathology Workshop within the category of B-cell lineage neoplasms’ transdifferentiation into histiocytic/dendritic cell neoplasms (HDCNs).

Methods

The workshop panel reviewed 29 cases, assigned consensus diagnoses, and summarized findings.

Results

The specific diagnoses of transdifferentiated HDCN tumors were histiocytic sarcoma (16); Langerhans cell histiocytosis/sarcoma (5); indeterminate DC tumor (1); and HDCN, unclassifiable (1). Approximately one-third of the patients reviewed had follicular lymphoma; lymphoblastic leukemia/lymphoma; or another B-cell lymphoma, most commonly chronic lymphocytic leukemia/small lymphocytic lymphoma. There was a 3:1 preponderance toward women, median patient age was 60 years, and the median interval between the initial diagnosis of B-cell lineage neoplasm and HDCN was 4 to 5 years. The submitted cases have demonstrated substantial heterogeneity as well as overlapping immunophenotypic and other features. Comprehensive genomic DNA sequencing revealed alterations enriched in the MAPK pathway. Based on shared and distinct alterations seen in HDCNs and the preceding lymphomas, both linear and divergent clonal evolutionary pathways were inferred. Furthermore, RNA sequencing performed in a subset of cases yielded new insights into markers that could be useful for more precise cell lineage identification. The panel has thus proposed an updated algorithm for HDCN lineage assignment. The outcome of transdifferentiated HDCNs was poor, but the MAPK signaling pathway emerges as a potentially attractive therapeutic target.

Conclusions

Transdifferentiated HDCNs demonstrate heterogeneity and pose diagnostic challenges with regard to exact classification, but the in-depth characterization of the submitted cases have added to our understanding of the secondary HDCNs transdifferentiated from B-cell lymphoma/leukemia. Continuous efforts focusing on deciphering the specific cell lineage and differentiation state of these tumors will be critical for their accurate classification. Comprehensive molecular characterization of HDCNs may be informative in this regard. With the list of novel pharmacologic inhibitors of the MAPK pathway continuing to expand, improved outcomes for HDCN can be expected.
Longevity of Post-Explantation Systemic Symptom Improvement and Potential Etiologies: Findings From the ASERF Systemic Symptoms in Women–Biospecimen Analysis Study: Part 4
Authors: Glicksman Caroline , McGuire Patricia , Kadin Marshall , Barnes Kirsten , Wixtrom Roger , Lawrence Marisa , Haws Melinda , Ferenz Sarah , Sung C James , Hamilton Robert G , Faasse Kate
Published: April 2023

Background

Breast Implant Illness (BII) describes a variety of symptoms reported by patients with breast implants. Biospecimens data revealed minimal statistical differences between BII and non-BII cohorts. Baseline analysis of PROMIS data demonstrated significant differences between the BII cohort and the 2 control cohorts.

Objectives

This study was designed to determine if patients in the BII cohort obtained any symptom improvement after explantation, whether symptom improvement was related to the type of capsulectomy, and which symptoms improved.

Methods

A prospective blinded study enrolled 150 consecutive patients divided equally into 3 cohorts. Baseline demographic data and a systemic symptoms survey, including PROMIS validated questionnaires, were obtained at baseline, 3 to 6 weeks, 6 months, and 1 year.

Results

A total of 150 patients were enrolled between 2019 and 2021. Follow-up at 1 year included 94% of the BII cohort and 77% of non-BII and mastopexy cohorts. At 1 year, 88% of patients showed at least partial symptom improvement, with a reduction of 2 to 20 symptoms. The PROMIS score in the BII cohort decreased at 1 year for anxiety, sleep disturbances, and fatigue. Systemic symptom improvement was noted out to 1 year in the BII cohort regardless of the type of capsulectomy performed.

Conclusions

Parts 1–3 in this series concluded that there were no consistent differences in biospecimen results between the cohorts. Unlike the data observed in the biospecimen analysis, BII patients had heightened symptoms and poorer PROMIS scores at baseline compared to the control cohorts. The reduction of negative expectations and a potential nocebo effect could contribute to this improvement.

Level of Evidence: 4
Population-based change-point detection for the identification of homozygosity islands
Authors: Prates Lucas , Lemes Renan B , Hünemeier Tábita , Leonardi Florencia
Published: April 2023

Motivation

This work is motivated by the problem of identifying homozygosity islands on the genome of individuals in a population. Our method directly tackles the issue of identification of the homozygosity islands at the population level, without the need of analysing single individuals and then combine the results, as is made nowadays in state-of-the-art approaches.

Results

We propose regularized offline change-point methods to detect changes in the parameters of a multidimensional distribution when we have several aligned, independent samples of fixed resolution. We present a penalized maximum likelihood approach that can be efficiently computed by a dynamic programming algorithm or approximated by a fast binary segmentation algorithm. Both estimators are shown to converge almost surely to the set of change-points without the need of specifying a priori the number of change-points. In simulation, we observed similar performances from the exact and greedy estimators. Moreover, we provide a new methodology for the selection of the regularization constant which has the advantage of being automatic, consistent, and less prone to subjective analysis.

Availability and implementation

The data used in the application are from the Human Genome Diversity Project (HGDP) and is publicly available. Algorithms were implemented using the R software R Core Team (R: A Language and Environment for Statistical Computing. Vienna (Austria): R Foundation for Statistical Computing, 2020.) in the R package blockcpd, found at https://github.com/Lucas-Prates/blockcpd.
Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling
Authors: Kaste Joshua A M , Shachar-Hill Yair
Published: April 2023

Motivation

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy.

Results

Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was169%–180% for high light conditions and 94%–103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant.

Availability and implementation

Code and data generated as part of this study are available from https://github.com/Gibberella/ArabidopsisGeneExpressionWeights.
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model
Authors: Zeng Yuansong , Wei Zhuoyi , Yuan Qianmu , Chen Sheng , Yu Weijiang , Lu Yutong , Gao Jianzhao , Yang Yuedong
Published: April 2023

Motivation

Identifying the B-cell epitopes is an essential step for guiding rational vaccine development and immunotherapies. Since experimental approaches are expensive and time-consuming, many computational methods have been designed to assist B-cell epitope prediction. However, existing sequence-based methods have limited performance since they only use contextual features of the sequential neighbors while neglecting structural information.

Results

Based on the recent breakthrough of AlphaFold2 in protein structure prediction, we propose GraphBepi, a novel graph-based model for accurate B-cell epitope prediction. For one protein, the predicted structure from AlphaFold2 is used to construct the protein graph, where the nodes/residues are encoded by ESM-2 learning representations. The graph is input into the edge-enhanced deep graph neural network (EGNN) to capture the spatial information in the predicted 3D structures. In parallel, a bidirectional long short-term memory neural networks (BiLSTM) are employed to capture long-range dependencies in the sequence. The learned low-dimensional representations by EGNN and BiLSTM are then combined into a multilayer perceptron for predicting B-cell epitopes. Through comprehensive tests on the curated epitope dataset, GraphBepi was shown to outperform the state-of-the-art methods by more than 5.5% and 44.0% in terms of AUC and AUPR, respectively. A web server is freely available at http://bio-web1.nscc-gz.cn/app/graphbepi.

Availability and implementation

The datasets, pre-computed features, source codes, and the trained model are available at https://github.com/biomed-AI/GraphBepi.
Reprogramming efficiency and pluripotency of mule iPSCs over its parents
Authors: Zhang Jia , Zhao Lixia , Fu Yuting , Liu Fangyuan , Wang Zixin , Li Yunxia , Zhao Gaoping , Sun Wei , Wu Baojiang , Song Yongli , Li Shaohua , Hao Chunxia , Wuyun Bilige , Wu Rihan , Liu Moning , Cao Guifang , Nashun Buhe , Surani M Azim , Sun Qingyuan , Bao Siqin , Liu Pentao , Li Xihe
Published: April 2023

The mule is the interspecific hybrid of horse and donkey and has hybrid vigor in muscular endurance, disease resistance, and longevity over its parents. Here, we examined adult fibroblasts of mule (MAFs) compared with the cells from their parents (donkey adult fibroblasts and horse adult fibroblasts) (each species has repeated three independent individuals) in proliferation, apoptosis, and glycolysis and found significant differences. We subsequently derived mule, donkey, and horse doxycycline (Dox)-independent induced pluripotent stem cells (miPSCs, diPSCs, and hiPSCs) from three independent individuals of each species and found that the reprogramming efficiency of MAFs was significantly higher than that of cells of donkey and horse. miPSCs, diPSCs, and hiPSCs all expressed the high levels of crucial endogenous pluripotency genes such as POU class 5 homeobox 1 (POU5F1, OCT4), SRY-box 2 (SOX2), and Nanog homeobox (NANOG) and propagated robustly in single-cell passaging. miPSCs exhibited faster proliferation and higher pluripotency and differentiation than diPSCs and hiPSCs, which were reflected in co-cultures and separate-cultures, teratoma formation, and chimera contribution. The establishment of miPSCs provides a unique research material for the investigation of “heterosis” and perhaps is more significant to study hybrid gamete formation.
Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling
Authors: Young Amber M , Van Buren Scott , Rashid Naim U
Published: April 2023

Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses. This procedure leverages fast matrix-based computations that make it ideally suited for DTU analysis with larger sample sizes. This method also allows for the testing of and adjustment for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty in the expression estimates for each transcript in RNA-seq data. We extend our CompDTU method to incorporate quantification uncertainty leveraging common output from RNA-seq expression quantification tool in a novel method CompDTUme. Through several power analyses, we show that CompDTU has excellent sensitivity and reduces false positive results relative to existing methods. Additionally, CompDTUme results in further improvements in performance over CompDTU with sufficient sample size for genes with high levels of quantification uncertainty, while also maintaining favorable speed and scalability. We motivate our methods using data from the Cancer Genome Atlas Breast Invasive Carcinoma data set, specifically using RNA-seq data from primary tumors for 740 patients with breast cancer. We show greatly reduced computation time from our new methods as well as the ability to detect several novel genes with significant DTU across different breast cancer subtypes.
The return of the lesion for localization and therapy
Authors: Joutsa Juho , Lipsman Nir , Horn Andreas , Cosgrove G Rees , Fox Michael D
Published: April 2023

Historically, pathological brain lesions provided the foundation for localization of symptoms and therapeutic lesions were used as a treatment for brain diseases. New medications, functional neuroimaging and deep brain stimulation have led to a decline in lesions in the past few decades. However, recent advances have improved our ability to localize lesion-induced symptoms, including localization to brain circuits rather than individual brain regions. Improved localization can lead to more precise treatment targets, which may mitigate traditional advantages of deep brain stimulation over lesions such as reversibility and tunability. New tools for creating therapeutic brain lesions such as high intensity focused ultrasound allow for lesions to be placed without a skin incision and are already in clinical use for tremor. Although there are limitations, and caution is warranted, improvements in lesion-based localization are refining our therapeutic targets and improved technology is providing new ways to create therapeutic lesions, which together may facilitate the return of the lesion.
Evaluating the role of anxiety on the association between irritable bowel syndrome and brain volumes: a mediation analysis in the UK Biobank cohort
Authors: Meng Peilin , Cheng Bolun , Pan Chuyu , Liu Li , Cheng Shiqiang , Yang Xuena , Chen Yujing , Li Chun’e , Zhang Huijie , Zhang Zhen , Zhang Jingxi , He Dan , Shi Sirong , Chu Xiaoge , Cai Qingqing , Zhang Na , Qin Xiaoyue , Zhao Yijing , Wei Wenming , Jia Yumeng , Wen Yan , Zhang Feng
Published: April 2023

There is a strong link between irritable bowel syndrome and brain volumes, yet, to date, research examining the mediators of this association has been little. Based on the phenotypic data of 15 248 participants from the UK Biobank, a two-stage mediation analysis was performed to assess the association among brain volumes, anxiety, and irritable bowel syndrome. In the first stage, we identified the candidate mediating role of anxiety for irritable bowel syndrome associated with brain volumes using regression models. Then, we quantified the magnitude of the mediation effects by evaluating the average causal-mediated effect and proportion of mediation through performing mediation analyses in the R package in the second stage. In the first stage, we identified the partly mediating role of anxiety in the association between irritable bowel syndrome and the volume of thalamus (Pleft = 1.16 × 10−4, Pright = 2.41 × 10−4), and grey matter (Pleft = 3.22 × 10−2, Pright = 1.18 × 10−2) in the VIIIa cerebellum. In the second stage, we observed that the proportion of the total effect of irritable bowel syndrome on volume of thalamus mediated by anxiety was 14.3% for the left region (βAverage causal-mediated effect = −0.008, PAverage causal-mediated effect = 0.004) and 14.6% for the right region (βAverage causal-mediated effect = −0.007, PAverage causal-mediated effect = 0.006). Anxiety mediated 30.8% for the left region (βAverage causal-mediated effect = −0.013, PAverage causal-mediated effect = 0.002) and 21.6% for the right region (βAverage causal-mediated effect = −0.010, PAverage causal-mediated effect x= 0.018) of the total effect of irritable bowel syndrome on the volume of grey matter in the VIIIa cerebellum. Our study revealed the indirect mediating role of anxiety in the association between irritable bowel syndrome and brain volumes, promoting our understanding of the functional mechanisms of irritable bowel syndrome and its related psychosocial factors.
Unemployment, workplace socialization, and electoral participation: evidence from Sweden
Authors: Österman Marcus , Brännlund Anton
Published: April 2023

How unemployment affects electoral participation is a archetypal question in political sociology and of particular relevance in economic crises; in the 1930s as well as during a pandemic. A frequent argument in the literature is that unemployment leads to political withdrawal as the unemployed have to focus on their economy and other personal matters. Some scholars, on the other hand, reason that unemployment triggers political mobilization through feelings of grievance and a strive to protest against leading politicians. However, existing empirical evidence is mixed and often suffers from limitations in data and research design. To make progress on this difficult empirical question, the present study leverages Swedish register data on turnout, spanning nine elections between 1970 and 2018. This extensive panel dataset enables us to more adequately address the causal status of the relationship by relying on the with-in individual variation in turnout. Our results report significant but modest negative effects of both unemployment in general and of losing a relatively well-paid job (job loss). The effects are driven by the young. We also find that the negative effect is less pronounced for those who have previously worked at a workplace where most colleagues participate, supporting a socialization mechanism.