bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recyclable soft photonic crystal film with overall improved circularly polarized luminescence
Authors: Shi Yonghong , Han Jianlei , Li Chengxi , Zhao Tonghan , Jin Xue , Duan Pengfei 
Published: September 2023

AbstractExisting circularly polarized luminescence materials can hardly satisfy the requirements of both large luminescence dissymmetry factor and high luminescent quantum yield, which hinders their practical applications. Here, we present a soft photonic crystal film embedded with chiral nanopores that possesses excellent circularly polarized luminescence performance with a high luminescence dissymmetry factor as well as a large luminescent quantum yield when loaded with various luminescent dyes. Benefitting from the retention of chiral nanopores imprinted from a chiral liquid crystal arrangement, the chiral soft photonic crystal film can not only endow dyes with chiral properties, but also effectively avoid severe aggregation of guest dye molecules. More importantly, the soft photonic crystal film can be recycled many times by loading and eluting guest dye molecules while retaining good stability as well as circularly polarized luminescence performance, enabling various applications, including smart windows, multi-color circularly polarized luminescence and anticounterfeiting.
PET-measured human dopamine synthesis capacity and receptor availability predict trading rewards and time-costs during foraging
Authors: Ianni Angela M. , Eisenberg Daniel P. , Boorman Erie D. , Constantino Sara M. , Hegarty Catherine E. , Gregory Michael D. , Masdeu Joseph C. , Kohn Philip D. , Behrens Timothy E. , Berman Karen F. 
Published: September 2023

AbstractForaging behavior requires weighing costs of time to decide when to leave one reward patch to search for another. Computational and animal studies suggest that striatal dopamine is key to this process; however, the specific role of dopamine in foraging behavior in humans is not well characterized. We use positron emission tomography (PET) imaging to directly measure dopamine synthesis capacity and D1and D2/3receptor availability in 57 healthy adults who complete a computerized foraging task. Using voxelwise data and principal component analysis to identify patterns of variation across PET measures, we show that striatal D1and D2/3receptor availability and a pattern of mesolimbic and anterior cingulate cortex dopamine function are important for adjusting the threshold for leaving a patch to explore, with specific sensitivity to changes in travel time. These findings suggest a key role for dopamine in trading reward benefits against temporal costs to modulate behavioral adaptions to changes in the reward environment critical for foraging.
Second breast cancer: recurrence score results, clinicopathologic characteristics, adjuvant treatments, and outcomes—exploratory analysis of the Clalit registry
Authors: Shachar Shlomit S. , Leviov Michelle , Yerushalmi Rinat , Drumea Karen , Tokar Margarita , Soussan-Gutman Lior , Bareket-Samish Avital , Sonnenblick Amir , Ben-Baruch Noa , Evron Ella , Gal-Yam Einav Nili , Paluch-Shimon Shani , Bar-Sela Gil , Goldvaser Hadar , Stemmer Salomon M. 
Published: September 2023

AbstractData on using the 21-gene Recurrence Score (RS) testing on second breast cancer (BC; second primary or local recurrence) are lacking. This cohort study examined patients with first and second BC, who underwent 21-gene testing both times. It included a ‘study-cohort’ (60 N0/N1mi/N1 ER + HER2‒ BC patients with ≥2 RS results >1 year apart) and a ‘general 21-gene-tested BC-cohort’ (2044 previously described N0/N1mi/N1 patients). The median time between the first and second BC was 5.2 (IQR, 3.1–7.1) years; the second BC was ipsilateral in 68%. Patient/tumor characteristics of the first- and second-BC in the ‘study-cohort’ were similar, except for the RS which was higher in the second BC (median [IQR]: 23 [17–30] vs 17 [14–22], p < 0.001). Overall, 56 patients had follow-up data, of whom 5 experienced distant recurrence (2 RS 11–25 patients and 3 RS 26–100 patients). Studies exploring the prognostic utility of the RS in this setting are warranted.
Graph deep learning accelerated efficient crystal structure search and feature extraction
Authors: Li Chuan-Nan , Liang Han-Pu , Zhang Xie , Lin Zijing , Wei Su-Huai 
Published: September 2023

AbstractStructural search and feature extraction are a central subject in modern materials design, the efficiency of which is currently limited, but can be potentially boosted by machine learning (ML). Here, we develop an ML-based prediction-analysis framework, which includes a symmetry-based combinatorial crystal optimization program (SCCOP) and a feature additive attribution model, to significantly reduce computational costs and to extract property-related structural features. Our method is highly accurate and predictive, and extracts structural features from desired structures to guide materials design. We first test SCCOP on 35 typical compounds to demonstrate its generality. As a case study, we apply our approach to a two-dimensional B-C-N system, which identifies 28 previously undiscovered stable structures out of 82 compositions; our analysis further establishes the structural features that contribute most to energy and bandgap. Compared to conventional approaches, SCCOP is about 10 times faster while maintaining a comparable accuracy. Our framework is generally applicable to all types of systems for precise and efficient structural search, providing insights into the relationship between ML-extracted structural features and physical properties.
A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery
Authors: Banik Suvo , Loefller Troy , Manna Sukriti , Chan Henry , Srinivasan Srilok , Darancet Pierre , Hexemer Alexander , Sankaranarayanan Subramanian K. R. S. 
Published: September 2023

AbstractMaterial properties share an intrinsic relationship with their structural attributes, making inverse design approaches crucial for discovering new materials with desired functionalities. Reinforcement Learning (RL) approaches are emerging as powerful inverse design tools, often functioning in discrete action spaces. This constrains their application in materials design problems, which involve continuous search spaces. Here, we introduce an RL-based framework CASTING (Continuous Action Space Tree Search for inverse design), that employs a decision tree-based Monte Carlo Tree Search (MCTS) algorithm with continuous space adaptation through modified policies and sampling. Using representative examples like Silver (Ag) for metals, Carbon (C) for covalent systems, and multicomponent systems such as graphane, boron nitride, and complex correlated oxides, we showcase its accuracy, convergence speed, and scalability in materials discovery and design. Furthermore, with the inverse design of super-hard Carbon phases, we demonstrate CASTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.
Mapping microstructure to shock-induced temperature fields using deep learning
Authors: Li Chunyu , Verduzco Juan Carlos , Lee Brian H. , Appleton Robert J. , Strachan Alejandro 
Published: September 2023

AbstractThe response of materials to shock loading is important to planetary science, aerospace engineering, and energetic materials. Thermally activated processes, including chemical reactions and phase transitions, are significantly accelerated by energy localization into hotspots. These result from the interaction of the shockwave with the materials’ microstructure and are governed by complex, coupled processes, including the collapse of porosity, interfacial friction, and localized plastic deformation. These mechanisms are not fully understood and the lack of models limits our ability to predict shock to detonation transition from chemistry and microstructure alone. We demonstrate that deep learning can be used to predict the resulting shock-induced temperature fields in composite materials obtained from large-scale molecular dynamics simulations with the initial microstructure as the only input. The accuracy of the Microstructure-Informed Shock-induced Temperature net (MISTnet) model is higher than the current state of the art and its evaluation requires a fraction of the computation cost.
A biomass map of the Brazilian Amazon from multisource remote sensing
Authors: Ometto Jean Pierre , Gorgens Eric Bastos , de Souza Pereira Francisca Rocha , Sato Luciane , de Assis Mauro Lúcio Rodrigures , Cantinho Roberta , Longo Marcos , Jacon Aline Daniele , Keller Michael 
Published: September 2023

AbstractThe Amazon Forest, the largest contiguous tropical forest in the world, stores a significant fraction of the carbon on land. Changes in climate and land use affect total carbon stocks, making it critical to continuously update and revise the best estimates for the region, particularly considering changes in forest dynamics. Forest inventory data cover only a tiny fraction of the Amazon region, and the coverage is not sufficient to ensure reliable data interpolation and validation. This paper presents a new forest above-ground biomass map for the Brazilian Amazon and the associated uncertainty both with a resolution of 250 meters and baseline for the satellite dataset the year of 2016 (i.e., the year of the satellite observation). A significant increase in data availability from forest inventories and remote sensing has enabled progress towards high-resolution biomass estimates. This work uses the largest airborne LiDAR database ever collected in the Amazon, mapping 360,000 km2 through transects distributed in all vegetation categories in the region. The map uses airborne laser scanning (ALS) data calibrated by field forest inventories that are extrapolated to the region using a machine learning approach with inputs from Synthetic Aperture Radar (PALSAR), vegetation indices obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, and precipitation information from the Tropical Rainfall Measuring Mission (TRMM). A total of 174 field inventories geolocated using a Differential Global Positioning System (DGPS) were used to validate the biomass estimations. The experimental design allowed for a comprehensive representation of several vegetation types, producing an above-ground biomass map varying from a maximum value of 518 Mg ha−1, a mean of 174 Mg ha−1, and a standard deviation of 102 Mg ha−1. This unique dataset enabled a better representation of the regional distribution of the forest biomass and structure, providing further studies and critical information for decision-making concerning forest conservation, planning, carbon emissions estimate, and mechanisms for supporting carbon emissions reductions.
A Global Feature-Rich Network Dataset of Cities and Dashboard for Comprehensive Urban Analyses
Authors: Yap Winston , Biljecki Filip 
Published: September 2023

AbstractUrban network analytics has become an essential tool for understanding and modeling the intricate complexity of cities. We introduce the Urbanity data repository to nurture this growing research field, offering a comprehensive, open spatial network resource spanning 50 major cities in 29 countries worldwide. Our workflow enhances OpenStreetMap networks with 40 + high-resolution indicators from open global sources such as street view imagery, building morphology, urban population, and points of interest, catering to a diverse range of applications across multiple fields. We extract streetscape semantic features from more than four million street view images using computer vision. The dataset’s strength lies in its thorough processing and validation at every stage, ensuring data quality and consistency through automated and manual checks. Accompanying the dataset is an interactive, web-based dashboard we developed which facilitates data access to even non-technical stakeholders. Urbanity aids various GeoAI and city comparative analyses, underscoring the growing importance of urban network analytics research.
Effect of recombination on genetic diversity of Caenorhabditis elegans
Authors: Hwang Ho-Yon , Wang Jiou 
Published: September 2023

AbstractGreater molecular divergence and genetic diversity are present in regions of high recombination in many species. Studies describing the correlation between variant abundance and recombination rate have long focused on recombination in the context of linked selection models, whereby interference between linked sites under positive or negative selection reduces genetic diversity in regions of low recombination. Here, we show that indels, especially those of intermediate sizes, are enriched relative to single nucleotide polymorphisms in regions of high recombination in C. elegans. To explain this phenomenon, we reintroduce an alternative model that emphasizes the mutagenic effect of recombination. To extend the analysis, we examine the variants with a phylogenetic context and discuss how different models could be examined together. The number of variants generated by recombination in natural populations could be substantial including possibly the majority of some indel subtypes. Our work highlights the potential importance of a mutagenic effect of recombination, which could have a significant role in the shaping of natural genetic diversity.
Simultaneous LC–MS/MS method for the quantitation of Azithromycin, Hydroxychloroquine and its metabolites in SARS-CoV-2(−/ +) populations using dried blood spots
Authors: Chhonker Yashpal S. , Aldhafiri Wafaa N. , Soni Dhruvkumar , Trivedi Neerja , Steinbronn Claire , Johnson Christine , Karita Helen C. Stankiewicz , Paasche-Orlow Michael K. , Barnabas Ruanne , Arnold Samuel L. , Murry Daryl J. 
Published: September 2023

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a global pandemic of coronavirus disease 2019 (COVID-19). Early in the pandemic, efforts were made to test the SARS-CoV-2 antiviral efficacy of repurposed medications that were already approved and available for other indications, including hydroxychloroquine (HCQ) and azithromycin (AZI). To reduce the risk of SARS-CoV-2 exposure for clinical-trial study participants and to conform with lockdowns and social distancing guidelines, biospecimen collection for HCQ and AZI included at-home dried blood spot (DBS) collection rather than standard venipuncture by trained clinicians. In this study, we developed and validated the first sensitive and selective simultaneous LC–MS/MS method to accurately quantitate the concentration of HCQ, HCQ metabolites (Desethylchloroquine [DCQ], Bisdesethylchloroquine [BDCQ], Monodesethylhydroxychloroquine [DHCQ]) and AZI extracted from DBS. The validated method was successfully applied for the quantification of over 2000 DBS specimens to evaluate the pharmacokinetic profile of AZI, HQC, and its metabolites. This new method has a small sample volume requirement (~ 10 µL), results in high sensitivity (1 ng/mL), and would facilitate remotely conducted therapeutic drug monitoring.
Neither sulfoxaflor, Crithidia bombi, nor their combination impact bumble bee colony development or field bean pollination
Authors: Straw Edward A. , Cini Elena , Gold Harriet , Linguadoca Alberto , Mayne Chloe , Rockx Joris , Brown Mark J. F. , Garratt Michael P. D. , Potts Simon G. , Senapathi Deepa 
Published: September 2023

AbstractMany pollinators, including bumble bees, are in decline. Such declines are known to be driven by a number of interacting factors. Decreases in bee populations may also negatively impact the key ecosystem service, pollination, that they provide. Pesticides and parasites are often cited as two of the drivers of bee declines, particularly as they have previously been found to interact with one another to the detriment of bee health. Here we test the effects of an insecticide, sulfoxaflor, and a highly prevalent bumble bee parasite, Crithidia bombi, on the bumble bee Bombus terrestris. After exposing colonies to realistic doses of either sulfoxaflor and/or Crithidia bombi in a fully crossed experiment, colonies were allowed to forage on field beans in outdoor exclusion cages. Foraging performance was monitored, and the impacts on fruit set were recorded. We found no effect of either stressor, or their interaction, on the pollination services they provide to field beans, either at an individual level or a whole colony level. Further, there was no impact of any treatment, in any metric, on colony development. Our results contrast with prior findings that similar insecticides (neonicotinoids) impact pollination services, and that sulfoxaflor impacts colony development, potentially suggesting that sulfoxaflor is a less harmful compound to bee health than neonicotinoids insecticides.
Repurposing disulfiram, an alcohol-abuse drug, in neuroblastoma causes KAT2A downregulation and in vivo activity with a water/oil emulsion
Authors: Beaudry Annie , Jacques-Ricard Simon , Darracq Anaïs , Sgarioto Nicolas , Garcia Araceli , García Teresita Rode , Lemieux William , Béland Kathie , Haddad Elie , Cordeiro Paulo , Duval Michel , McGraw Serge , Richer Chantal , Caron Maxime , Marois François , St-Onge Pascal , Sinnett Daniel , Banquy Xavier , Raynal Noël J.-M. 
Published: September 2023

AbstractNeuroblastoma, the most common type of pediatric extracranial solid tumor, causes 10% of childhood cancer deaths. Despite intensive multimodal treatment, the outcomes of high-risk neuroblastoma remain poor. We urgently need to develop new therapies with safe long-term toxicity profiles for rapid testing in clinical trials. Drug repurposing is a promising approach to meet these needs. Here, we investigated disulfiram, a safe and successful chronic alcoholism treatment with known anticancer and epigenetic effects. Disulfiram efficiently induced cell cycle arrest and decreased the viability of six human neuroblastoma cell lines at half-maximal inhibitory concentrations up to 20 times lower than its peak clinical plasma level in patients treated for chronic alcoholism. Disulfiram shifted neuroblastoma transcriptome, decreasing MYCN levels and activating neuronal differentiation. Consistently, disulfiram significantly reduced the protein level of lysine acetyltransferase 2A (KAT2A), drastically reducing acetylation of its target residues on histone H3. To investigate disulfiram’s anticancer effects in an in vivo model of high-risk neuroblastoma, we developed a disulfiram-loaded emulsion to deliver the highly liposoluble drug. Treatment with the emulsion significantly delayed neuroblastoma progression in mice. These results identify KAT2A as a novel target of disulfiram, which directly impacts neuroblastoma epigenetics and is a promising candidate for repurposing to treat pediatric neuroblastoma.
Jahn–Teller distortion in Sr2FeO4: group-theoretical analysis and hybrid DFT calculations
Authors: Zvejnieks Guntars , Mastrikov Yuri , Gryaznov Denis 
Published: September 2023

AbstractWe present theoretical justification for distorted Ruddlesden–Popper (RP) phases of the first-order by using hybrid density functional theory (DFT) calculations and group-theoretical analysis. We, thus, demonstrate the existence of the Jahn–Teller effect around an Fe$$^{4\texttt {+}}$$

4
+

ion in Sr$$_{2}$$

2

FeO$$_{4}$$

4

. On the calculation side, we have established a combination of Wu–Cohen (WC) exchange and Perdew-Wang (PW) correlation in a three-parameter functional WC3PW, giving the most accurate description of Sr$$_{2}$$

2

FeO$$_{4}$$

4

from the comparison of three hybrid DFT functionals. Self-consistently obtained Hartree–Fock exact exchange of 0.16 demonstrates consistent results with the experimental literature data. Importantly, we explain conditions for co-existing proper and pseudo-Jahn–Teller effects from the crystalline orbitals, symmetry-mode analysis and irreps products. Moreover, phonon frequency calculations support and confirm the results of symmetry-mode analysis. In particular, the symmetry-mode analysis identifies a dominating irreducible representation of the Jahn-Teller mode (X2) and corresponding space group (SG) of ground state structure (SG Cmce model). Therefore, the usually suggested high-symmetry tetragonal crystal structure (SG I4/mmm model) is higher in energy by 121 meV/f.u. (equivalent to the Jahn-Teller stabilization energy) compared with the distorted low-symmetry structure (SG Cmce model). We also present diffraction patterns for the two crystal symmetries to discuss the differences. Therefore, our results shed light on the existence of low-symmetry RP phases and make possible direct comparisons with future experiments.
Innate immune dysregulation in multisystem inflammatory syndrome in children (MIS-C)
Authors: Isaza-Correa Johana , Ryan Laura , Kelly Lynne , Allen John , Melo Ashanty , Jones Jennifer , Huggard Dean , Ryan Emer , Ó Maoldomhnaigh Cilian , Geoghehan Sarah , Gavin Patrick , Leahy Timothy Ronan , Butler Karina , Freyne Bridget , Molloy Eleanor J. 
Published: September 2023

AbstractMIS-C is a systemic inflammation disorder with poorly characterised immunopathological mechanisms. We compared changes in the systemic immune response in children with MIS-C (n = 12, 5–13 years) to healthy controls (n = 14, 5–15 years). Analysis was done in whole blood treated with LPS. Expression of CD11b and Toll-like receptor-4 (TLR4) in neutrophils and monocytes were analysed by flow cytometry. Serum cytokines (IL-1β, IL-2, IL-6, IL-8, IL-10, IL-Ira, TNF-α, TNF-β, IFN-Υ, VEGF, EPO and GM-CSF) and mRNA levels of inflammasome molecules (NLRP3, ASC and IL-1β) were evaluated. Subpopulations of lymphocytes (CD3+, CD19+, CD56+, CD4+, CD8+, TCR Vδ1+, TCR Vδ2+) were assessed at basal levels. Absolute counts of neutrophils and NLR were high in children with MIS-C while absolute counts of lymphocytes were low. Children with MIS-C had increased levels of IL-6, IL-10, TNF-β and VEGF serum cytokines at the basal level, and significantly increased TNF-β post-LPS, compared to controls. IL-1RA and EPO decreased at baseline and post-LPS in MIS-C patients compared to controls. The percentage of CD3+ cells, NK cells and Vδ1 was lower while B cells were higher in children with MIS-C than in controls. Dysregulated immune response in children with MIS-C was evident and may be amenable to immunomodulation.
The simplified Kirchhoff network model (SKNM): a cell-based reaction–diffusion model of excitable tissue
Authors: Jæger Karoline Horgmo , Tveito Aslak 
Published: September 2023

AbstractCell-based models of excitable tissues offer the advantage of cell-level precision, which cannot be achieved using traditional homogenized electrophysiological models. However, this enhanced accuracy comes at the cost of increased computational demands, necessitating the development of efficient cell-based models. The widely-accepted bidomain model serves as the standard in computational cardiac electrophysiology, and under certain anisotropy ratio conditions, it is well known that it can be reduced to the simpler monodomain model. Recently, the Kirchhoff Network Model (KNM) was developed as a cell-based counterpart to the bidomain model. In this paper, we aim to demonstrate that KNM can be simplified using the same steps employed to derive the monodomain model from the bidomain model. We present the cell-based Simplified Kirchhoff Network Model (SKNM), which produces results closely aligned with those of KNM while requiring significantly less computational resources.