bluuebunny/crossref_metadata_2025_split huggingface dataset:
Male-female communication enhances release of extracellular vesicles leading to high fertility in Drosophila
Authors: Sanchez-Lopez Javier Arturo , Twena Shai , Apel Ido , Kornhaeuser Shani Chen , Chasnitsky Michael , Miklosi Andras G. , Vega-Dominguez Perla J. , Shephard Alex , Hefetz Amir , Heifetz Yael 
Published: August 2022

AbstractThe female reproductive tract (female-RT) must decipher the repertoire of molecular cues received from the male during copulation in order to activate and coordinate tract functionality necessary for high fertility. In Drosophila, this modulation is partially driven by spermathecal secretory cells (SSC). The SSC are a layer of cuboidal secretory glandular cells surrounding the spermatheca capsule where sperm is stored. It is unclear, however, how the SSC regulate the system’s activity. Here we show that mating activates the secretory machinery of the SSC. The SSC release a heterogeneous population of extracellular vesicles (EVs) which is involved in initiating and managing the increase in egg-laying, and possibly sperm storage. Moreover, sperm and male accessory gland proteins are essential for such mating-mediated SSC activity. Thus, mating regulates secretory/endocytic pathways required for trafficking of vesicles to SSC-female-RT target sites, which modulate and coordinate reproductive tract activity to achieve high fertility.
FACT modulates the conformations of histone H2A and H2B N-terminal tails within nucleosomes
Authors: Tsunaka Yasuo , Ohtomo Hideaki , Nishimura Yoshifumi 
Published: August 2022

AbstractGene expression is regulated by the modification and accessibility of histone tails within nucleosomes. The histone chaperone FACT (facilitate chromatin transcription), comprising SPT16 and SSRP1, interacts with nucleosomes through partial replacement of DNA with the phosphorylated acidic intrinsically disordered (pAID) segment of SPT16; pAID induces an accessible conformation of the proximal histone H3 N-terminal tail (N-tail) in the unwrapped nucleosome with FACT. Here, we use NMR to probe the histone H2A and H2B tails in the unwrapped nucleosome. Consequently, both the H2A and H2B N-tails on the pAID-proximal side bind to pAID with robust interactions, which are important for nucleosome assembly with FACT. Furthermore, the conformations of these N-tails on the distal DNA-contact site are altered from those in the canonical nucleosome. Our findings highlight that FACT both proximally and distally regulates the conformations of the H2A and H2B N-tails in the asymmetrically unwrapped nucleosome.
Learning the dynamics of metamaterials from diffracted waves with convolutional neural networks
Authors: Zhai Yuxin , Kwon Hyung-Suk , Choi Yunseok , Kovacevich Dylan , Popa Bogdan-Ioan 
Published: August 2022

AbstractConventional methods used to identify the dynamical properties of unknown media from scattered mechanical waves rely on analytical or numerical manipulations of the wave equation. These methods show their limitations in scenarios where the analyzed medium is moderately sized and the diffraction from the material edges influences the scattered fields significantly, such as non-destructive diagnostics and metamaterial characterization. Here, we show that convolutional neural networks can interpret the diffracted fields and learn the mapping between the scattered fields and all the effective material parameters including mass density and stiffness tensors from a small set of numerical simulations. Furthermore, networks trained with synthetic data can process physical measurements and are very robust to measurement errors. More importantly, the trained network provides insight into the dynamic behavior of matter including quantitative measures of the scattered field sensitivity to each material property and how the sensitivity changes depending on the material under test.
A widely distributed genus of soil Acidobacteria genomically enriched in biosynthetic gene clusters
Authors: Crits-Christoph Alexander , Diamond Spencer , Al-Shayeb Basem , Valentin-Alvarado Luis , Banfield Jillian F 
Published: August 2022

Abstract
Bacteria of the phylum Acidobacteria are one of the most abundant groups across soil ecosystems, yet they are represented by comparatively few sequenced genomes, leaving gaps in our understanding of their metabolic diversity. Recently, genomes of Acidobacteria species with unusually large repertoires of biosynthetic gene clusters (BGCs) were reconstructed from grassland soil metagenomes, but the degree to which species with this trait are widespread is still unknown. To investigate this, we assembled 46 metagenome-assembled genomes recovered from permanently saturated organic-rich soils of a vernal (spring) pool ecosystem in Northern California. We obtained high and medium-quality draft genomes for three novel species from Candidatus Angelobacter (a proposed subdivision 1 Acidobacterial genus), a genus that is genomically enriched in genes for specialized metabolite biosynthesis. Acidobacteria were particularly abundant in the vernal pool sediments, and a Ca. Angelobacter species was the most abundant bacterial species detected in some samples. We identified numerous diverse biosynthetic gene clusters in these genomes, and also in five additional genomes from other publicly available soil metagenomes for other related Ca. Angelobacter species. Metabolic analysis indicates that Ca. Angelobacter likely are aerobes that ferment organic carbon, with potential to contribute to carbon compound turnover in soils. Using metatranscriptomics, we identified in situ metabolic activity and expression of specialized metabolic traits for two species from this genus. In conclusion, we expand genomic sampling of the uncultivated Ca. Angelobacter, and show that they represent common and sometimes highly abundant members of dry and saturated soil communities, with a high degree of capacity for synthesis of diverse specialized metabolites.
Modified unified power flow controller for medium voltage distribution networks
Authors: Abdelrahman Mohamed A. , Yang Peng , Ming Wenlong , Wu Jianzhong , Jenkins Nick 
Published: August 2022

AbstractA conventional unified power flow controllers (UPFCs) can provide power flow control and voltage regulation in medium voltage (MV) distribution networks using partially rated converters. However, one of the main challenges of using the conventional UPFC is the unique design of the series interfacing transformer. This paper investigates a modified topology of a UPFC suitable for MV distribution networks. The modified UPFC does not need an interfacing series transformer. Hence, it offers a smaller size, lighter weight, and less cost than the conventional UPFC. It consists of single‐phase back‐to‐back series and shunt voltage source converters. The series converters are connected to a distribution network without a series transformer, while the shunt converters are interfaced using a three‐phase shunt transformer. The power ratings of the series and shunt converters were investigated considering a distribution network with a low X/R ratio. The modified UPFC was modelled in MATLAB Simulink and was connected to a two‐busbar distribution network and the enhanced IEEE 33‐bus distribution network. The results showed the ability of the modified UPFC to independently control active and reactive power in a distribution feeder by processing a fraction of the power transfer through the converters.
Active contour driven by adaptive‐scale local‐energy signed pressure force function based on bias correction for medical image segmentation
Authors: Liu Huaxiang , Fu Youyao , Zhang Shiqing , Liu Jun , Fang Jiangxiong 
Published: August 2022

AbstractThis paper presents an active contour model driven by an adaptive‐scale local‐energy signed pressure force (ALSPF) function based on bias correction for segmenting medical images with intensity inhomogeneity. Firstly, a local energy‐driven signed pressure force (LESPF) function is designed as the driving force to extract local image features, which can effectively deal with intensity inhomogeneity. Secondly, to avid selecting the neighbourhood size in the LESPF function, a multi‐scale adaptive selection schema is put forward to adaptively choose the local window size according to the degree of intensity inhomogeneity. Finally, a novel single‐well potential function proved to be a strictly monotonic function is designed to ensure the stable movement of the neighbourhood points in the vicinity of the evolution curve, which can not only avoid the re‐initialization process but also enhance. Experiments on synthetic and medical images demonstrate that the proposed model is more robust than the popular ACMs for segmenting images with intensity inhomogeneity. The code is available at the website: https://github.com/HuaxiangLiu/ALSPF
Structural analogue-based protein structure domain assembly assisted by deep learning
Authors: Peng Chun-Xiang , Zhou Xiao-Gen , Xia Yu-Hao , Liu Jun , Hou Ming-Hua , Zhang Gui-Jun 
Published: August 2022

AbstractMotivationWith the breakthrough of AlphaFold2, the protein structure prediction problem has made remarkable progress through deep learning end-to-end techniques, in which correct folds could be built for nearly all single-domain proteins. However, the full-chain modelling appears to be lower on average accuracy than that for the constituent domains and requires higher demand on computing hardware, indicating the performance of full-chain modelling still needs to be improved. In this study, we investigate whether the predicted accuracy of the full-chain model can be further improved by domain assembly assisted by deep learning.ResultsIn this article, we developed a structural analogue-based protein structure domain assembly method assisted by deep learning, named SADA. In SADA, a multi-domain protein structure database was constructed for the full-chain analogue detection using individual domain models. Starting from the initial model constructed from the analogue, the domain assembly simulation was performed to generate the full-chain model through a two-stage differential evolution algorithm guided by the energy function with an inter-residue distance potential predicted by deep learning. SADA was compared with the state-of-the-art domain assembly methods on 356 benchmark proteins, and the average TM-score of SADA models is 8.1% and 27.0% higher than that of DEMO and AIDA, respectively. We also assembled 293 human multi-domain proteins, where the average TM-score of the full-chain model after the assembly by SADA is 1.1% higher than that of the model by AlphaFold2. To conclude, we find that the domains often interact in the similar way in the quaternary orientations if the domains have similar tertiary structures. Furthermore, homologous templates and structural analogues are complementary for multi-domain protein full-chain modelling.Availability and implementationhttp://zhanglab-bioinf.com/SADASupplementary informationSupplementary data are available at Bioinformatics online.
How is Social Care Provided in Adult Prisons in England and Wales?
Authors: Walton Holly , Tomini Sonila M , Sherlaw-Johnson Chris , Ng Pei Li , Fulop Naomi J 
Published: August 2022

AbstractThere is variation in provision of social care in prisons. Our research aimed to understand variation across adult prisons in England and Wales, including: (1) what social care is provided? (2) who delivers social care? (3) what peer support initiatives are used? (4) what social care indicators are relevant? and (5) are there differences between prison type and social care provision? We analysed Her Majesty’s Inspectorate of Prisons (HMIP) reports (published 2017–2020) from 102 prisons. From these reports we extracted and analysed data on social care provision. Elements of social care are not consistently delivered; need assessments (81.4 per cent) and referrals (75.5 per cent) were most frequently reported. Different providers (health care/social care/prison) deliver social care. Forty-one prisons (40.2 per cent) included peer support (formal to informal). We found no notable differences between prison categories and social care delivery, although, within category D prisons, a significantly larger proportion of those with a disability reported receiving support they needed. Inspection reports highlighted that prison social care should mirror community social care, but we could not fully evaluate this due to reporting issues. Social care provision varies; effectiveness of different models is not yet known. We provide recommendations to improve social care reporting within HMIP reports.
Quantifying research interests in 7,521 mammalian species with h-index: a case study
Authors: Tam Jessica , Lagisz Malgorzata , Cornwell Will , Nakagawa Shinichi 
Published: August 2022

Abstract

Background
Taxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, a systematic quantification of the research interest that the scientific community has allocated to individual species remains a big data problem. Scalable approaches are needed to integrate biodiversity data sets and bibliometric methods across large numbers of species. The outputs of these analyses are important for identifying understudied species and directing future research to fill these gaps.

Findings
In this study, we used the species h-index to quantity the research interest in 7,521 species of mammals. We tested factors potentially driving species h-index, by using a Bayesian phylogenetic generalized linear mixed model (GLMM). We found that a third of the mammals had a species h-index of zero, while a select few had inflated research interest. Further, mammals with higher species h-index had larger body masses; were found in temperate latitudes; had their humans uses documented, including domestication; and were in lower-risk International Union for Conservation of Nature Red List categories. These results surprisingly suggested that critically endangered mammals are understudied. A higher interest in domesticated species suggested that human use is a major driver and focus in mammalian scientific literature.

Conclusions
Our study has demonstrated a scalable workflow and systematically identified understudied species of mammals, as well as identified the likely drivers of this taxonomic bias in the literature. This case study can become a benchmark for future research that asks similar biological and meta-research questions for other taxa.
Association between household composition and severe COVID-19 outcomes in older people by ethnicity: an observational cohort study using the OpenSAFELY platform
Authors: Wing Kevin , Grint Daniel J , Mathur Rohini , Gibbs Hamish P , Hickman George , Nightingale Emily , Schultze Anna , Forbes Harriet , Nafilyan Vahé , Bhaskaran Krishnan , Williamson Elizabeth , House Thomas , Pellis Lorenzo , Herrett Emily , Gautam Nileesa , Curtis Helen J , Rentsch Christopher T , Wong Angel Y S , MacKenna Brian , Mehrkar Amir , Bacon Seb , Douglas Ian J , Evans Stephen J W , Tomlinson Laurie , Goldacre Ben , Eggo Rosalind M 
Published: August 2022

AbstractBackgroundEthnic differences in the risk of severe COVID-19 may be linked to household composition. We quantified the association between household composition and risk of severe COVID-19 by ethnicity for older individuals.MethodsWith the approval of NHS England, we analysed ethnic differences in the association between household composition and severe COVID-19 in people aged 67 or over in England. We defined households by number of age-based generations living together, and used multivariable Cox regression stratified by location and wave of the pandemic and accounted for age, sex, comorbidities, smoking, obesity, housing density and deprivation. We included 2 692 223 people over 67 years in Wave 1 (1 February 2020–31 August 2020) and 2 731 427 in Wave 2 (1 September 2020–31 January 2021).ResultsMultigenerational living was associated with increased risk of severe COVID-19 for White and South Asian older people in both waves [e.g. Wave 2, 67+ living with three other generations vs 67+-year-olds only: White hazard ratio (HR) 1.61 95% CI 1.38–1.87, South Asian HR 1.76 95% CI 1.48–2.10], with a trend for increased risks of severe COVID-19 with increasing generations in Wave 2. There was also an increased risk of severe COVID-19 in Wave 1 associated with living alone for White (HR 1.35 95% CI 1.30–1.41), South Asian (HR 1.47 95% CI 1.18–1.84) and Other (HR 1.72 95% CI 0.99–2.97) ethnicities, an effect that persisted for White older people in Wave 2.ConclusionsBoth multigenerational living and living alone were associated with severe COVID-19 in older adults. Older South Asian people are over-represented within multigenerational households in England, especially in the most deprived settings, whereas a substantial proportion of White older people live alone. The number of generations in a household, number of occupants, ethnicity and deprivation status are important considerations in the continued roll-out of COVID-19 vaccination and targeting of interventions for future pandemics.
Non-dissipative and structure-preserving emulators via spherical optimization
Authors: Dai Dihan , Epshteyn Yekaterina , Narayan Akil 
Published: August 2022

Abstract
Approximating a function with a finite series, e.g., involving polynomials or trigonometric functions, is a critical tool in computing and data analysis. The construction of such approximations via now-standard approaches like least squares or compressive sampling does not ensure that the approximation adheres to certain convex linear structural constraints, such as positivity or monotonicity. Existing approaches that ensure such structure are norm-dissipative and this can have a deleterious impact when applying these approaches, e.g., when numerical solving partial differential equations. We present a new framework that enforces via optimization such structure on approximations and is simultaneously norm-preserving. This results in a conceptually simple convex optimization problem on the sphere, but the feasible set for such problems can be very complex. We establish well-posedness of the optimization problem through results on spherical convexity and design several spherical-projection-based algorithms to numerically compute the solution. Finally, we demonstrate the effectiveness of this approach through several numerical examples.
Associations of antimicrobial use with antimicrobial susceptibility at the calf level in bacteria isolated from the respiratory and digestive tracts of veal calves before slaughter
Authors: Becker Jens , Perreten Vincent , Schüpbach-Regula Gertraud , Stucki Dimitri , Steiner Adrian , Meylan Mireille 
Published: August 2022

Abstract

Objectives
Antimicrobial drugs are frequently administered in veal calves, but investigations on associations with antimicrobial susceptibility of bacteria are scarce and convey partly contradictory findings. The aim of this study was to investigate associations of antimicrobial use (AMU) during the fattening period with antimicrobial susceptibility shortly before slaughter.

Methods
Detailed treatment data of 1905 veal calves from 38 farms were collected prospectively during monthly farm visits for 1 year (n = 1864 treatments, n = 535 visits); 1582 Escherichia coli, 1059 Pasteurella multocida and 315 Mannheimia haemolytica were isolated from rectal and nasopharyngeal swabs collected before slaughter and subjected to antimicrobial susceptibility testing by microdilution. Associations of antimicrobial treatments with resistant isolates were investigated at the calf level.

Results
Associations of AMU with antimicrobial resistance were observed using generalized linear models. For E. coli, the odds of being resistant were increased with increased AMU (OR 1.36 when number of treatments &gt;1, P = 0.066). Use of tetracyclines was associated with resistance to tetracycline (OR 1.86, P &lt; 0.001) and use of penicillins was associated with resistance to ampicillin (OR 1.66, P = 0.014). No significant associations were observed for P. multocida (use of aminoglycosides: OR 3.66 for resistance to spectinomycin, P = 0.074). For M. haemolytica, the odds of being resistant were increased with increased AMU (OR 4.63, P &lt; 0.001), and use of tetracyclines was associated with resistance to tetracycline (OR 6.49, P &lt; 0.001).

Conclusions
Occurrence of resistant bacteria shortly before slaughter was associated with AMU in veal calves. Prudent and appropriate use may contribute to limit the selection of resistant bacteria on veal farms.
The impact of the COVID-19 pandemic on foreign investment and investment arbitration: from energy transition disrupted to the path forward to a greener future
Authors: Arlota Carolina 
Published: August 2022

Abstract
Foreign investment in the energy sector is complex during the best of times. The challenges posed by the COVID-19 pandemic (and its intertwined economic crises) increased competition for foreign investment and strengthened the perennial quest for climate justice. The pandemic added complexity to both domestic and international spheres of governance, which led to calls for a suspension or even a cancellation of arbitration claims involving foreign investments. As developing and developed countries compete for financial resources to transition to a carbon-neutral society, such a suspension or cancellation is of academic and practical interest. Accordingly, this article discusses the impact of the pandemic on foreign investment in the energy sector, focusing on investment claims. It assesses competing views involving the proposed revisions (namely, suspensions and cancellations) and their consequences based on a law and economics perspective. This article also examines how foreign investments that align with the United Nations Sustainable Development Goals may foster the transition to a greener future. Ultimately, this article offers relevant insights that are likely to be applicable to critical future disruptions, whether they occur due to global economic crises or climate-related emergencies.
Dynamic response of photorespiration in fluctuating light environments
Authors: Fu Xinyu , Walker Berkley J 
Published: August 2022

Abstract
Photorespiration is a dynamic process that is intimately linked to photosynthetic carbon assimilation. There is a growing interest in understanding carbon assimilation during dynamic conditions, but the role of photorespiration under such conditions is unclear. In this review, we discuss recent work relevant to the function of photorespiration under dynamic conditions, with a special focus on light transients. This work reveals that photorespiration is a fundamental component of the light induction of assimilation where variable diffusive processes limit CO2 exchange with the atmosphere. Additionally, metabolic interactions between photorespiration and the C3 cycle may help balance fluxes under dynamic light conditions. We further discuss how the energy demands of photorespiration present special challenges to energy balancing during dynamic conditions. We finish the review with an overview of why regulation of photorespiration may be important under dynamic conditions to maintain appropriate fluxes through metabolic pathways related to photorespiration such as nitrogen and one-carbon metabolism.