bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrical Resistivity of Fe and Fe‐3 wt%P at 5 GPa With Implications for the Moon's Core Conductivity and Dynamo
Authors: Yin Yuan , Wang Lin , Zhai Shuangmeng , Fei Yingwei 
Published: April 2022

AbstractA high‐magnetic field once existed in the early history of the Moon, suggesting the core once possessed a thermally driven dynamo. The thermal conductivity of core materials is a significant parameter of the dynamo. The lunar core composition is thought to be iron or iron‐alloyed with some light elements (e.g., S, P, Si, and C), but its transport properties remain uncertain. We measured the electrical resistivity of iron and Fe‐3 wt%P alloys at 5 GPa and high temperatures. Apart from the quasi four‐point technique, the four‐probe van der Pauw technique was also employed to measure the resistivity of pure iron. Adding ∼3 wt% phosphorus to iron slightly increases the resistivity at 5 GPa and 1000–1500 K due to the impurity effect. The resistivity of Fe‐3 wt%P alloys increases at the onset of melting. Via the Wiedemann‐Franz law, the thermal conductivity at the lunar core‐mantle boundary (CMB) is estimated to be 28.6–34.2 Wm−1K−1 for a light‐element free core and 31.5 ± 1.9 Wm−1K−1 for a phosphorus‐bearing (∼3 wt% P) core. Therefore, small amounts of phosphorus in the lunar core slightly impact its thermal conductivity. The estimated conductive heat flow across the lunar CMB varies from 4.5 to 5.7 GW, and the adiabatic heat flux varies from 3.3 to 4.2 mW/m2, depending on the core's composition (Fe or Fe‐3 wt%P). Integrating our results with previous lunar core evolution models, we suggest that a thermally driven dynamo persisted until 3.63–3.88 Ga ago.
Graphene-driving strain engineering to enable strain-free epitaxy of AlN film for deep ultraviolet light-emitting diode
Authors: Chang Hongliang , Liu Zhetong , Yang Shenyuan , Gao Yaqi , Shan Jingyuan , Liu Bingyao , Sun Jingyu , Chen Zhaolong , Yan Jianchang , Liu Zhiqiang , Wang Junxi , Gao Peng , Li Jinmin , Liu Zhongfan , Wei Tongbo 
Published: April 2022

AbstractThe energy-efficient deep ultraviolet (DUV) optoelectronic devices suffer from critical issues associated with the poor quality and large strain of nitride material system caused by the inherent mismatch of heteroepitaxy. In this work, we have prepared the strain-free AlN film with low dislocation density (DD) by graphene (Gr)-driving strain-pre-store engineering and a unique mechanism of strain-relaxation in quasi-van der Waals (QvdW) epitaxy is presented. The DD in AlN epilayer with Gr exhibits an anomalous sawtooth-like evolution during the whole epitaxy process. Gr can help to enable the annihilation of the dislocations originated from the interface between AlN and Gr/sapphire by impelling a lateral two-dimensional growth mode. Remarkably, it can induce AlN epilayer to pre-store sufficient tensile strain during the early growth stage and thus compensate the compressive strain caused by hetero-mismatch. Therefore, the low-strain state of the DUV light-emitting diode (DUV-LED) epitaxial structure is realized on the strain-free AlN template with Gr. Furthermore, the DUV-LED with Gr demonstrate 2.1 times enhancement of light output power and a better stability of luminous wavelength compared to that on bare sapphire. An in-depth understanding of this work reveals diverse beneficial impacts of Gr on nitride growth and provides a novel strategy of relaxing the vital requirements of hetero-mismatch in conventional heteroepitaxy.
Engaging children and young people on the potential role of artificial intelligence in medicine
Authors: Visram Sheena , Leyden Deirdre , Annesley Oceiah , Bappa Dauda , Sebire Neil J. 
Published: April 2022

Abstract
Introduction
There is increasing interest in Artificial Intelligence (AI) and its application to medicine. Perceptions of AI are less well-known, notably amongst children and young people (CYP). This workshop investigates attitudes towards AI and its future applications in medicine and healthcare at a specialised paediatric hospital using practical design scenarios.

Method
Twenty-one members of a Young Persons Advisory Group for research contributed to an engagement workshop to ascertain potential opportunities, apprehensions, and priorities.

Results
When presented as a selection of practical design scenarios, we found that CYP were more open to some applications of AI in healthcare than others. Human-centeredness, governance and trust emerged as early themes, with empathy and safety considered as important when introducing AI to healthcare. Educational workshops with practical examples using AI to help, but not replace humans were suggested to address issues, build trust, and effectively communicate about AI.

Conclusion
Whilst policy guidelines acknowledge the need to include children and young people to develop AI, this requires an enabling environment for human-centred AI involving children and young people with lived experiences of healthcare. Future research should focus on building consensus on enablers for an intelligent healthcare system designed for the next generation, which fundamentally, allows co-creation.

Impact

Children and young people (CYP) want to be included to share their insights about the development of research on the potential role of Artificial Intelligence (AI) in medicine and healthcare and are more open to some applications of AI than others.

Whilst it is acknowledged that a research gap on involving and engaging CYP in developing AI policies exists, there is little in the way of pragmatic and practical guidance for healthcare staff on this topic.

This requires research on enabling environments for ongoing digital cooperation to identify and prioritise unmet needs in the application and development of AI.
Variegation of autism related traits across seven neurogenetic disorders
Authors: Lee Nancy Raitano , Niu Xin , Zhang Fengqing , Clasen Liv S. , Kozel Beth A. , Smith Ann C. M. , Wallace Gregory L. , Raznahan Armin 
Published: April 2022

AbstractGene dosage disorders (GDDs) constitute a major class of genetic risks for psychopathology, but there is considerable debate regarding the extent to which different GDDs induce different psychopathology profiles. The current research speaks to this debate by compiling and analyzing dimensional measures of several autism-related traits (ARTs) across seven diverse GDDs. The sample included 350 individuals with one of 7 GDDs, as well as reference idiopathic autism spectrum disorder (ASD;n = 74) and typically developing control (TD;n = 171) groups. The GDDs were: Down, Williams–Beuren, and Smith–Magenis (DS, WS, SMS) syndromes, and varying sex chromosome aneuploidies (“plusX”, “plusXX”, “plusY”, “plusXY”). The Social Responsiveness Scale (SRS-2) was used to measure ARTs at different levels of granularity—item, subscale, and total. General linear models were used to examine ART profiles in GDDs, and machine learning was used to predict genotype from SRS-2 subscales and items. These analyses were completed with and without covariation for cognitive impairment. Twelve of all possible 21 pairwise GDD group contrasts showed significantly different ART profiles (7/21 when co-varying for IQ, all Bonferroni-corrected). Prominent GDD–ART associations in post hoc analyses included relatively preserved social motivation in WS and relatively low levels of repetitive behaviors in plusX. Machine learning revealed that GDD group could be predicted with plausible accuracy (~60–80%) even after controlling for IQ. GDD effects on ARTs are influenced by GDD subtype and ART dimension. This observation has consequences for mechanistic, clinical, and translational aspects of psychiatric neurogenetics.
Inhibition of the CEBPβ-NFκB interaction by nanocarrier-packaged Carnosic acid ameliorates glia-mediated neuroinflammation and improves cognitive function in an Alzheimer’s disease model
Authors: Yi-Bin Wang , Xiang Li , Bing Yang , Qi Zhang , Fei-Tong Jiao , Minghong Wang , Xiangxiang Zhang , Le Kang , Yan Li , Ping Sui , Yufei Gao , Ye Xu , Chun-Yan Wang 
Published: April 2022

AbstractNeuroinflammation occurs early in Alzheimer’s disease (AD). The initial stage of AD is related to glial dysfunction, which contributes to impairment of Aβ clearance and disruption of synaptic connection. CEBPβ, a member of the CCAAT-enhancer-binding protein (CEBP) family, modulates the expression of inflammation-associated genes, and its expression is elevated in brains undergoing degeneration and injured brains. However, the mechanism underlying CEBPβ-mediated chronic inflammation in AD is unclear. In this study, we observed that increases in the levels of nuclear CEBPβ facilitated the interaction of CEBPβ with the NFκB p65 subunit, increasing the transcription of proinflammatory cytokines in the APP/PS1 mouse brain. Oral administration of nanocarrier-packaged carnosic acid (CA) reduced the aberrant activation of microglia and astrocytes and diminished mature IL-1β, TNFα and IL-6 production in the APP/PS1 mouse brain. CA administration reduced β-amyloid (Aβ) deposition and ameliorated cognitive impairment in APP/PS1 mice. We observed that CA blocked the interaction of CEBPβ with NFκB p65, and chromatin immunoprecipitation revealed that CA reduced the transcription of the NFκB target genes TNFα and IL-6. We confirmed that CA alleviated inflammatory mediator-induced neuronal degeneration and reduced Aβ secretion by inhibiting the CEBPβ-NFκB signalling pathway in vitro. Sulfobutyl ether-beta-cyclodextrin (SBEβCD) was used as the encapsulation agent for the CA-loaded nanocarrier to overcome the poor water solubility and enhance the brain bioavailability of CA. The CA nanoparticles (NPs) had no obvious toxicity. We demonstrated a feasible SBEβCD-based nanodelivery system targeting the brain. Our data provide experimental evidence that CA-loaded NPs are potential therapeutic agents for AD treatment.
Virally programmed extracellular vesicles sensitize cancer cells to oncolytic virus and small molecule therapy
Authors: Wedge Marie-Eve , Jennings Victoria A. , Crupi Mathieu J. F. , Poutou Joanna , Jamieson Taylor , Pelin Adrian , Pugliese Giuseppe , de Souza Christiano Tanese , Petryk Julia , Laight Brian J. , Boileau Meaghan , Taha Zaid , Alluqmani Nouf , McKay Hayley E. , Pikor Larissa , Khan Sarwat Tahsin , Azad Taha , Rezaei Reza , Austin Bradley , He Xiaohong , Mansfield David , Rose Elaine , Brown Emily E. F. , Crawford Natalie , Alkayyal Almohanad , Surendran Abera , Singaravelu Ragunath , Roy Dominic G. , Migneco Gemma , McSweeney Benjamin , Cottee Mary Lynn , Jacobus Egon J. , Keller Brian A. , Yamaguchi Takafumi N. , Boutros Paul C. , Geoffrion Michele , Rayner Katey J. , Chatterjee Avijit , Auer Rebecca C. , Diallo Jean-Simon , Gibbings Derrick , tenOever Benjamin R. , Melcher Alan , Bell John C. , Ilkow Carolina S. 
Published: April 2022

AbstractRecent advances in cancer therapeutics clearly demonstrate the need for innovative multiplex therapies that attack the tumour on multiple fronts. Oncolytic or “cancer-killing” viruses (OVs) represent up-and-coming multi-mechanistic immunotherapeutic drugs for the treatment of cancer. In this study, we perform an in-vitro screen based on virus-encoded artificial microRNAs (amiRNAs) and find that a unique amiRNA, herein termed amiR-4, confers a replicative advantage to the VSVΔ51 OV platform. Target validation of amiR-4 reveals ARID1A, a protein involved in chromatin remodelling, as an important player in resistance to OV replication. Virus-directed targeting of ARID1A coupled with small-molecule inhibition of the methyltransferase EZH2 leads to the synthetic lethal killing of both infected and uninfected tumour cells. The bystander killing of uninfected cells is mediated by intercellular transfer of extracellular vesicles carrying amiR-4 cargo. Altogether, our findings establish that OVs can serve as replicating vehicles for amiRNA therapeutics with the potential for combination with small molecule and immune checkpoint inhibitor therapy.
Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation
Authors: Fang Zheng , Qin Hongqiang , Mao Jiawei , Wang Zhongyu , Zhang Na , Wang Yan , Liu Luyao , Nie Yongzhan , Dong Mingming , Ye Mingliang 
Published: April 2022

AbstractGlycopeptides with unusual glycans or poor peptide backbone fragmentation in tandem mass spectrometry are unaccounted for in typical site-specific glycoproteomics analysis and thus remain unidentified. Here, we develop a glycoproteomics tool, Glyco-Decipher, to address these issues. Glyco-Decipher conducts glycan database-independent peptide matching and exploits the fragmentation pattern of shared peptide backbones in glycopeptides to improve the spectrum interpretation. We benchmark Glyco-Decipher on several large-scale datasets, demonstrating that it identifies more peptide-spectrum matches than Byonic, MSFragger-Glyco, StrucGP and pGlyco 3.0, with a 33.5%-178.5% increase in the number of identified glycopeptide spectra. The database-independent and unbiased profiling of attached glycans enables the discovery of 164 modified glycans in mouse tissues, including glycans with chemical or biological modifications. By enabling in-depth characterization of site-specific protein glycosylation, Glyco-Decipher is a promising tool for advancing glycoproteomics analysis in biological research.
Enhancing biofuels production by engineering the actin cytoskeleton in Saccharomyces cerevisiae
Authors: Liu Hui , Zhou Pei , Qi Mengya , Guo Liang , Gao Cong , Hu Guipeng , Song Wei , Wu Jing , Chen Xiulai , Chen Jian , Chen Wei , Liu Liming 
Published: April 2022

AbstractSaccharomyces cerevisiae is widely employed as a cell factory for the production of biofuels. However, product toxicity has hindered improvements in biofuel production. Here, we engineer the actin cytoskeleton in S. cerevisiae to increase both the cell growth and production of n-butanol and medium-chain fatty acids. Actin cable tortuosity is regulated using an n-butanol responsive promoter-based autonomous bidirectional signal conditioner in S. cerevisiae. The budding index is increased by 14.0%, resulting in the highest n-butanol titer of 1674.3 mg L−1. Moreover, actin patch density is fine-tuned using a medium-chain fatty acid responsive promoter-based autonomous bidirectional signal conditioner. The intracellular pH is stabilized at 6.4, yielding the highest medium-chain fatty acids titer of 692.3 mg L−1 in yeast extract peptone dextrose medium. Engineering the actin cytoskeleton in S. cerevisiae can efficiently alleviate biofuels toxicity and enhance biofuels production.
Phase 1b study of berzosertib and cisplatin in patients with advanced triple-negative breast cancer
Authors: Telli Melinda L. , Tolaney Sara M. , Shapiro Geoffrey I. , Middleton Mark , Lord Simon R. , Arkenau Hendrik Tobias , Tutt Andrew , Abramson Vandana , Dean Emma , Haddad Tufia C. , Wesolowski Robert , Ferrer-Playan Jordi , Goddemeier Thomas , Grombacher Thomas , Dong Jennifer , Fleuranceau-Morel Patricia , Diaz-Padilla Ivan , Plummer Ruth 
Published: April 2022

AbstractPlatinum derivatives are commonly used for the treatment of patients with metastatic triple-negative breast cancer (TNBC). However, resistance often develops, leading to treatment failure. This expansion cohort (part C2) of the previously reported phase 1b trial (NCT02157792) is based on the recommended phase 2 dose of the combination of the ataxia-telangiectasia and Rad3-related (ATR) inhibitor berzosertib and cisplatin observed in patients with advanced solid tumors, including TNBC. Forty-seven patients aged ≥18 years with advanced TNBC received cisplatin (75 mg/m2; day 1) and berzosertib (140 mg/m2; days 2 and 9), in 21-day cycles. Berzosertib was well tolerated, with a similar toxicity profile to that reported previously for this combination. The overall response rate (90% confidence interval) was 23.4% (13.7, 35.8). No relevant associations were observed between response and gene alterations. Further studies combining ATR inhibitors with platinum compounds may be warranted in highly selected patient populations.
Deciphering Bitcoin Blockchain Data by Cohort Analysis
Authors: Liu Yulin , Zhang Luyao , Zhao Yinhong 
Published: April 2022

AbstractBitcoin is a peer-to-peer electronic payment system that has rapidly grown in popularity in recent years. Usually, the complete history of Bitcoin blockchain data must be queried to acquire variables with economic meaning. This task has recently become increasingly difficult, as there are over 1.6 billion historical transactions on the Bitcoin blockchain. It is thus important to query Bitcoin transaction data in a way that is more efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in the social sciences. Specifically, we query and process the Bitcoin transaction input and output data within each daily cohort. This enables us to create datasets and visualizations for some key Bitcoin transaction indicators, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the cumulative unspent transaction output (UTXO). We provide a computationally feasible approach for characterizing Bitcoin transactions that paves the way for future economic studies of Bitcoin.
Fusarium species isolated from post-hatchling loggerhead sea turtles (Caretta caretta) in South Africa
Authors: Greeff-Laubscher Mariska R. , Jacobs Karin 
Published: April 2022

AbstractSpecies in the Fusarium solani species complex are fast growing, environmental saprophytic fungi. Members of this genus are filamentous fungi with a wide geographical distribution. Fusarium keratoplasticum and F. falciforme have previously been isolated from sea turtle nests and have been associated with high egg mortality rates. Skin lesions were observed in a number of stranded, post-hatchling loggerhead sea turtles (Caretta caretta) in a rehabilitation facility in South Africa. Fungal hyphae were observed in epidermal scrapes of affected turtles and were isolated. The aim of this study was to characterise the Fusarium species that were isolated from these post-hatchling loggerhead sea turtles (Caretta caretta) that washed up on beaches along the South African coastline. Three gene regions were amplified and sequenced, namely the internal transcribed spacer region (ITS), a part of the nuclear large subunit (LSU), and part of the translation elongation factor 1 α (tef1) gene region. Molecular characteristics of strains isolated during this study showed high similarity with Fusarium isolates, which have previously been associated with high egg mortality rates in loggerhead sea turtles. This is the first record of F. keratoplasticum, F. falciforme and F. crassum isolated from stranded post-hatchling loggerhead sea turtles in South Africa.
Comparing protein–protein interaction networks of SARS-CoV-2 and (H1N1) influenza using topological features
Authors: Khojasteh Hakimeh , Khanteymoori Alireza , Olyaee Mohammad Hossein 
Published: April 2022

AbstractSARS-CoV-2 pandemic first emerged in late 2019 in China. It has since infected more than 298 million individuals and caused over 5 million deaths globally. The identification of essential proteins in a protein–protein interaction network (PPIN) is not only crucial in understanding the process of cellular life but also useful in drug discovery. There are many centrality measures to detect influential nodes in complex networks. Since SARS-CoV-2 and (H1N1) influenza PPINs pose 553 common human proteins. Analyzing influential proteins and comparing these networks together can be an effective step in helping biologists for drug-target prediction. We used 21 centrality measures on SARS-CoV-2 and (H1N1) influenza PPINs to identify essential proteins. We applied principal component analysis and unsupervised machine learning methods to reveal the most informative measures. Appealingly, some measures had a high level of contribution in comparison to others in both PPINs, namely Decay, Residual closeness, Markov, Degree, closeness (Latora), Barycenter, Closeness (Freeman), and Lin centralities. We also investigated some graph theory-based properties like the power law, exponential distribution, and robustness. Both PPINs tended to properties of scale-free networks that expose their nature of heterogeneity. Dimensionality reduction and unsupervised learning methods were so effective to uncover appropriate centrality measures.
An agent-based model reveals lost person behavior based on data from wilderness search and rescue
Authors: Hashimoto Amanda , Heintzman Larkin , Koester Robert , Abaid Nicole 
Published: April 2022

AbstractThousands of people are reported lost in the wilderness in the United States every year and locating these missing individuals as rapidly as possible depends on coordinated search and rescue (SAR) operations. As time passes, the search area grows, survival rate decreases, and searchers are faced with an increasingly daunting task of searching large areas in a short amount of time. To optimize the search process, mathematical models of lost person behavior with respect to landscape can be used in conjunction with current SAR practices. In this paper, we introduce an agent-based model of lost person behavior which allows agents to move on known landscapes with behavior defined as independent realizations of a random variable. The behavior random variable selects from a distribution of six known lost person reorientation strategies to simulate the agent’s trajectory. We systematically simulate a range of possible behavior distributions and find a best-fit behavioral profile for a hiker with the International Search and Rescue Incident Database. We validate these results with a leave-one-out analysis. This work represents the first time-discrete model of lost person dynamics validated with data from real SAR incidents and has the potential to improve current methods for wilderness SAR.
A prenatal acoustic signal of heat affects thermoregulation capacities at adulthood in an arid-adapted bird
Authors: Pessato Anaïs , McKechnie Andrew E. , Mariette Mylene M. 
Published: April 2022

AbstractUnderstanding animal physiological adaptations for tolerating heat, and the causes of inter-individual variation, is key for predicting climate change impacts on biodiversity. Recently, a novel mechanism for transgenerational heat adaptation was identified in a desert-adapted bird, where parents acoustically signal hot conditions to embryos. Prenatal exposure to “heat-calls” adaptively alters zebra finch development and their thermal preferences in adulthood, suggesting a long-term shift towards a heat-adapted phenotype. However, whether such acoustic experience improves long-term thermoregulatory capacities is unknown. We measured metabolic rate (MR), evaporative water loss (EWL) and body temperature in adults exposed to a stepped profile of progressively higher air temperatures (Ta) between 27 and 44 °C. Remarkably, prenatal acoustic experience affected heat tolerance at adulthood, with heat-call exposed individuals more likely to reach the highest Ta in morning trials. This was despite MR and EWL reaching higher levels at the highest Ta in heat-call individuals, partly driven by a stronger metabolic effect of moderate activity. At lower Ta, however, heat-call exposed individuals had greater relative water economy, as expected. They also better recovered mass lost during morning trials. We therefore provide the first evidence that prenatal acoustic signals have long-term consequences for heat tolerance and physiological adaptation to heat.