bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiwavelength analysis of Galactic Supernova Remnants
Authors: Sharma P. , Ou Z. , Henry-Cadrot C. , Dubos C. , Suomijärvi T. 
Published: April 2023

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
‘Dangerous Women’
Authors: Eidinow Esther 
Published: April 2023

AbstractThis 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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

AbstractMotivationIdentifying 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.ResultsBased 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 implementationThe 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

Abstract
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

SummaryDifferential 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.