bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cdh5-mediated Fpn1 deletion exerts neuroprotective effects during the acute phase and inhibitory effects during the recovery phase of ischemic stroke
Authors: Zheng Huiwen , Guo Xin , Kang Shaomeng , Li Zhongda , Tian Tian , Li Jianhua , Wang Fudi , Yu Peng , Chang Shiyang , Chang Yan-zhong 
Published: February 2023

AbstractIschemic stroke is associated with high mortality and morbidity rates worldwide. However, the molecular mechanisms underlying the neuronal damage incurred by stroke victims remain unclear. It has previously been reported that ischemic stroke can induce an increase in the levels of brain iron, which is an important factor of in the associated brain damage. Ferroportin 1 (FPN1), the only known cellular iron export protein, is found in brain microvascular endothelial cells (BMVECs) at the blood-brain barrier, and is considered the gateway for entry of plasma iron into the central nervous system. Despite the connection of brain iron to neuronal damage, the role of BMVECs FPN1 in ischemic stroke remains unexplored. Herein, we conditionally deleted Fpn1 in mouse endothelial cells (ECs), using VE-cadherin-Cre transgenic mice, and explored the impact on brain iron homeostasis after stroke. Our data demonstrated that Fpn1 knockout in ECs decreased the brain iron levels in mice, attenuated the oxidative stress and inflammatory responses after stroke, and inhibited both ferroptosis and apoptosis, ultimately alleviating neurological impairment and decreasing cerebral infarct volume during the acute phase of ischemic stroke. By contrast, we found that Fpn1 knockout in ECs delayed the recovery of neurological function in mice following ischemic stroke. We also found that ECs Fpn1 knockout decreased the brain iron levels after stroke, exacerbated glial cell proliferation, and inhibited neuronal development, indicating that the diminished brain iron levels hindered the repair of neural injury in mice. In conclusion, our findings reveal a dual consequence of FPN1 deficiency in ECs in the development of ischemic stroke. More specifically, iron deficiency initially exerts a neuroprotective effect during the acute phase of ischemic stroke but inhibits recovery during the later stages. Our findings are important to the development of iron- or FPN1-targeting therapeutics for the treatment of ischemic stroke.
A density functional theory for ecology across scales
Authors: Trappe Martin-I. , Chisholm Ryan A. 
Published: February 2023

AbstractEcology lacks a holistic approach that can model phenomena across temporal and spatial scales, largely because of the challenges in modelling systems with a large number of interacting constituents. This hampers our understanding of complex ecosystems and the impact that human interventions (e.g., deforestation, wildlife harvesting and climate change) have on them. Here we use density functional theory, a computational method for many-body problems in physics, to develop a computational framework for ecosystem modelling. Our methods accurately fit experimental and synthetic data of interacting multi-species communities across spatial scales and can project to unseen data. As the key concept we establish and validate a cost function that encodes the trade-offs between the various ecosystem components. We show how this single general modelling framework delivers predictions on par with established, but specialised, approaches for systems from predatory microbes to territorial flies to tropical tree communities. Our density functional framework thus provides a promising avenue for advancing our understanding of ecological systems.
Oxidation of metallic Cu by supercritical CO2 and control synthesis of amorphous nano-metal catalysts for CO2 electroreduction
Authors: Chen Chunjun , Yan Xupeng , Wu Yahui , Zhang Xiudong , Liu Shoujie , Zhang Fanyu , Sun Xiaofu , Zhu Qinggong , Zheng Lirong , Zhang Jing , Xing Xueqing , Wu Zhonghua , Han Buxing 
Published: February 2023

AbstractAmorphous nano-metal catalysts often exhibit appealing catalytic properties, because the intrinsic linear scaling relationship can be broken. However, accurate control synthesis of amorphous nano-metal catalysts with desired size and morphology is a challenge. In this work, we discover that Cu(0) could be oxidized to amorphous CuxO species by supercritical CO2. The formation process of the amorphous CuxO is elucidated with the aid of machine learning. Based on this finding, a method to prepare Cu nanoparticles with an amorphous shell is proposed by supercritical CO2 treatment followed by electroreduction. The unique feature of this method is that the size of the particles with amorphous shell can be easily controlled because their size depends on that of the original crystal Cu nanoparticles. Moreover, the thickness of the amorphous shell can be easily controlled by CO2 pressure and/or treatment time. The obtained amorphous Cu shell exhibits high selectivity for C2+ products with the Faradaic efficiency of 84% and current density of 320 mA cm−2. Especially, the FE of C2+ oxygenates can reach up to 65.3 %, which is different obviously from the crystalline Cu catalysts.
Hierarchical graph learning for protein–protein interaction
Authors: Gao Ziqi , Jiang Chenran , Zhang Jiawen , Jiang Xiaosen , Li Lanqing , Zhao Peilin , Yang Huanming , Huang Yong , Li Jia 
Published: February 2023

AbstractProtein-Protein Interactions (PPIs) are fundamental means of functions and signalings in biological systems. The massive growth in demand and cost associated with experimental PPI studies calls for computational tools for automated prediction and understanding of PPIs. Despite recent progress, in silico methods remain inadequate in modeling the natural PPI hierarchy. Here we present a double-viewed hierarchical graph learning model, HIGH-PPI, to predict PPIs and extrapolate the molecular details involved. In this model, we create a hierarchical graph, in which a node in the PPI network (top outside-of-protein view) is a protein graph (bottom inside-of-protein view). In the bottom view, a group of chemically relevant descriptors, instead of the protein sequences, are used to better capture the structure-function relationship of the protein. HIGH-PPI examines both outside-of-protein and inside-of-protein of the human interactome to establish a robust machine understanding of PPIs. This model demonstrates high accuracy and robustness in predicting PPIs. Moreover, HIGH-PPI can interpret the modes of action of PPIs by identifying important binding and catalytic sites precisely. Overall, “HIGH-PPI [https://github.com/zqgao22/HIGH-PPI]” is a domain-knowledge-driven and interpretable framework for PPI prediction studies.
Hyperbolic band topology with non-trivial second Chern numbers
Authors: Zhang Weixuan , Di Fengxiao , Zheng Xingen , Sun Houjun , Zhang Xiangdong 
Published: February 2023

AbstractTopological band theory establishes a standardized framework for classifying different types of topological matters. Recent investigations have shown that hyperbolic lattices in non-Euclidean space can also be characterized by hyperbolic Bloch theorem. This theory promotes the investigation of hyperbolic band topology, where hyperbolic topological band insulators protected by first Chern numbers have been proposed. Here, we report a new finding on the construction of hyperbolic topological band insulators with a vanished first Chern number but a non-trivial second Chern number. Our model possesses the non-abelian translational symmetry of {8,8} hyperbolic tiling. By engineering intercell couplings and onsite potentials of sublattices in each unit cell, the non-trivial bandgaps with quantized second Chern numbers can appear. In experiments, we fabricate two types of finite hyperbolic circuit networks with periodic boundary conditions and partially open boundary conditions to detect hyperbolic topological band insulators. Our work suggests a new way to engineer hyperbolic topological states with higher-order topological invariants.
Photocatalytic CO2 reduction with aminoanthraquinone organic dyes
Authors: Lei Qinqin , Yuan Huiqing , Du Jiehao , Ming Mei , Yang Shuang , Chen Ya , Lei Jingxiang , Han Zhiji 
Published: February 2023

AbstractThe direct utilization of solar energy to convert CO2 into renewable chemicals remains a challenge. One essential difficulty is the development of efficient and inexpensive light-absorbers. Here we show a series of aminoanthraquinone organic dyes to promote the efficiency for visible light-driven CO2 reduction to CO when coupled with an Fe porphyrin catalyst. Importantly, high turnover numbers can be obtained for both the photosensitizer and the catalyst, which has not been achieved in current light-driven systems. Structure-function study performed with substituents having distinct electronic effects reveals that the built-in donor-acceptor property of the photosensitizer significantly promotes the photocatalytic activity. We anticipate this study gives insight into the continued development of advanced photocatalysts for solar energy conversion.
A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data
Authors: De Falco Antonio , Caruso Francesca , Su Xiao-Dong , Iavarone Antonio , Ceccarelli Michele 
Published: February 2023

AbstractSingle-cell RNA sequencing is the reference technology to characterize the composition of the tumor microenvironment and to study tumor heterogeneity at high resolution. Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single-cell RNA-seq data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to datasets encompassing 106 samples and 93,322 cells from different tumor types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.
A monofluoride ether-based electrolyte solution for fast-charging and low-temperature non-aqueous lithium metal batteries
Authors: Zhang Guangzhao , Chang Jian , Wang Liguang , Li Jiawei , Wang Chaoyang , Wang Ruo , Shi Guoli , Yu Kai , Huang Wei , Zheng Honghe , Wu Tianpin , Deng Yonghong , Lu Jun 
Published: February 2023

AbstractThe electrochemical stability window of the electrolyte solution limits the energy content of non-aqueous lithium metal batteries. In particular, although electrolytes comprising fluorinated solvents show good oxidation stability against high-voltage positive electrode active materials such as LiNi0.8Co0.1Mn0.1O2 (NCM811), the ionic conductivity is adversely affected and, thus, the battery cycling performance at high current rates and low temperatures. To address these issues, here we report the design and synthesis of a monofluoride ether as an electrolyte solvent with Li-F and Li-O tridentate coordination chemistries. The monofluoro substituent (-CH2F) in the solvent molecule, differently from the difluoro (-CHF2) and trifluoro (-CF3) counterparts, improves the electrolyte ionic conductivity without narrowing the oxidation stability. Indeed, the electrolyte solution with the monofluoride ether solvent demonstrates good compatibility with positive and negative electrodes in a wide range of temperatures (i.e., from −60 °C to +60 °C) and at high charge/discharge rates (e.g., at 17.5 mA cm−2). Using this electrolyte solution, we assemble and test a 320 mAh Li||NCM811 multi-layer pouch cell, which delivers a specific energy of 426 Wh kg−1 (based on the weight of the entire cell) and capacity retention of 80% after 200 cycles at 0.8/8 mA cm−2 charge/discharge rate and 30 °C.
Mid-infrared single-pixel imaging at the single-photon level
Authors: Wang Yinqi , Huang Kun , Fang Jianan , Yan Ming , Wu E , Zeng Heping 
Published: February 2023

AbstractSingle-pixel cameras have recently emerged as promising alternatives to multi-pixel sensors due to reduced costs and superior durability, which are particularly attractive for mid-infrared (MIR) imaging pertinent to applications including industry inspection and biomedical diagnosis. To date, MIR single-pixel photon-sparse imaging has yet been realized, which urgently calls for high-sensitivity optical detectors and high-fidelity spatial modulators. Here, we demonstrate a MIR single-photon computational imaging with a single-element silicon detector. The underlying methodology relies on nonlinear structured detection, where encoded time-varying pump patterns are optically imprinted onto a MIR object image through sum-frequency generation. Simultaneously, the MIR radiation is spectrally translated into the visible region, thus permitting infrared single-photon upconversion detection. Then, the use of advanced algorithms of compressed sensing and deep learning allows us to reconstruct MIR images under sub-Nyquist sampling and photon-starving illumination. The presented paradigm of single-pixel upconversion imaging is featured with single-pixel simplicity, single-photon sensitivity, and room-temperature operation, which would establish a new path for sensitive imaging at longer infrared wavelengths or terahertz frequencies, where high-sensitivity photon counters and high-fidelity spatial modulators are typically hard to access.
Ssu72 phosphatase is essential for thermogenic adaptation by regulating cytosolic translation
Authors: Park Eun-Ji , Kim Hyun-Soo , Lee Do-Hyoung , Kim Su-Min , Yoon Joon-Sup , Lee Ji-Min , Im Se Jin , Lee Ho , Lee Min-Woo , Lee Chang-Woo 
Published: February 2023

AbstractBrown adipose tissue (BAT) plays a pivotal role in maintaining body temperature and energy homeostasis. BAT dysfunction is associated with impaired metabolic health. Here, we show that Ssu72 phosphatase is essential for mRNA translation of genes required for thermogenesis in BAT. Ssu72 is found to be highly expressed in BAT among adipose tissue depots, and the expression level of Ssu72 is increased upon acute cold exposure. Mice lacking adipocyte Ssu72 exhibit cold intolerance during acute cold exposure. Mechanistically, Ssu72 deficiency alters cytosolic mRNA translation program through hyperphosphorylation of eIF2α and reduces translation of mitochondrial oxidative phosphorylation (OXPHOS) subunits, resulting in mitochondrial dysfunction and defective thermogenesis in BAT. In addition, metabolic dysfunction in Ssu72-deficient BAT returns to almost normal after restoring Ssu72 expression. In summary, our findings demonstrate that cold-responsive Ssu72 phosphatase is involved in cytosolic translation of key thermogenic effectors via dephosphorylation of eIF2α in brown adipocytes, providing insights into metabolic benefits of Ssu72.
Policy relevant health related liveability indicator datasets for addresses in Australia’s 21 largest cities
Authors: Higgs Carl , Lowe Melanie , Hooper Paula , Mavoa Suzanne , Arundel Jonathan , Gunn Lucy , Simons Koen , Giles-Corti Billie 
Published: February 2023

AbstractMeasuring and monitoring the spatial distribution of liveability is crucial to ensure that implemented urban and transport planning decisions support health and wellbeing. Spatial liveability indicators can be used to ensure these decisions are effective, equitable and tracked across time. The 2018 Australian National Liveability Study datasets comprise a suite of policy-relevant health-related spatial indicators of local neighbourhood liveability and amenity access estimated for residential address points and administrative areas across Australia’s 21 most populous cities. The indicators and measures encompass access to community and health services, social infrastructure, employment, food, housing, public open space, transportation, walkability and overall liveability. This national ’baseline’ liveability indicators dataset for residential address points and areas can be further linked with surveys containing geocoded participant locations, as well as Census data for areas from the Australian Statistical Geography Standard. The datasets will be of interest to planners, policy makers and researchers interested in modelling and mapping the spatial distribution of urban environmental exposures and their relationship with health and other outcomes.
Differential expression of interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) in Alzheimer's disease and HIV-1 associated neurocognitive disorders
Authors: Garces Armando , Martinez Bryan , De La Garza Roberto , Roy Deepa , Vallee Kaylie-Anna , Fields Jerel Adam , Moore David J. , Rodrigo Hansapani , Roy Upal 
Published: February 2023

AbstractThe United Nations projects that one in every six people will be over the age of 65 by the year 2050. With a rapidly aging population, the risk of Alzheimer's disease (AD) becomes a major concern. AD is a multifactorial disease that involves neurodegeneration in the brain with mild dementia and deficits in memory and other cognitive domains. Additionally, it has been established that individuals with Human Immunodeficiency Virus-1 (HIV-1) experience a 5 to 10-year accelerated aging and an increased risk of developing HIV-associated neurocognitive disorders (HAND). Despite a significant amount of clinical evidence pointing towards a potential overlap between neuropathogenic processes in HAND and AD, the underlying epigenetic link between these two diseases is mostly unknown. This study is focused on identifying differentially expressed genes observed in both AD and HAND using linear regression models and a more robust significance analysis of microarray. The results established that the dysregulated type 1 and 2 interferon pathways observed in both AD and HAND contribute to the similar pathologies of these diseases within the brain. The current study identifies the important roles of interferon pathways in AD and HAND, a relationship that may be useful for earlier detection in the future.
Assessment of foraminal decompression following discoplasty using a combination of ex vivo testing and numerical tools
Authors: Techens Chloé , Bereczki Ferenc , Montanari Sara , Lazary Aron , Cristofolini Luca , Eltes Peter Endre 
Published: February 2023

AbstractPercutaneous Cement Discoplasty (PCD) is a minimally invasive surgical technique to treat degenerated intervertebral discs. When the disc is severely degenerated, the vacuum observed in place of the nucleus pulposus can be filled with bone cement to restore the disc height, open the foramen space, and relieve pain. This study aimed to evaluate the foramen geometry change due to PCD, in the loaded spine. Cadaveric spines (n = 25) were tested in flexion and extension while Digital Image Correlation (DIC) measured displacements and deformations. Tests were performed on simulated pre-operative condition (nucleotomy) and after PCD. Registering DIC images and the 3D specimen geometry from CT scans, a 3D model of the specimens aligned in the experimental pose was obtained for nucleotomy and PCD. Foramen space volume was geometrically measured for both conditions. The volume of cement injected was measured to explore correlation with the change of foramen space. PCD induced a significant overall foraminal decompression in both flexion (foramen space increased by 835 ± 1289 mm3, p = 0.001) and extension (1205 ± 1106 mm3, p < 0.001), confirming that the expected improvements of PCD show also during spine motion. Furthermore, in extension when the foramen is the most challenged, the impact of PCD on the foramen correlated with the injected cement volume.
Disentangling clustering configuration intricacies for divergently selected chicken breeds
Authors: Vakhrameev Anatoly B. , Narushin Valeriy G. , Larkina Tatyana A. , Barkova Olga Y. , Peglivanyan Grigoriy K. , Dysin Artem P. , Dementieva Natalia V. , Makarova Alexandra V. , Shcherbakov Yuri S. , Pozovnikova Marina V. , Bondarenko Yuri V. , Griffin Darren K. , Romanov Michael N. 
Published: February 2023

AbstractDivergently selected chicken breeds are of great interest not only from an economic point of view, but also in terms of sustaining diversity of the global poultry gene pool. In this regard, it is essential to evaluate the classification (clustering) of varied chicken breeds using methods and models based on phenotypic and genotypic breed differences. It is also important to implement new mathematical indicators and approaches. Accordingly, we set the objectives to test and improve clustering algorithms and models to discriminate between various chicken breeds. A representative portion of the global chicken gene pool including 39 different breeds was examined in terms of an integral performance index, i.e., specific egg mass yield relative to body weight of females. The generated dataset was evaluated within the traditional, phenotypic and genotypic classification/clustering models using the k-means method, inflection points clustering, and admixture analysis. The latter embraced SNP genotype datasets including a specific one focused on the performance-associated NCAPG-LCORL locus. The k-means and inflection points analyses showed certain discrepancies between the tested models/submodels and flaws in the produced cluster configurations. On the other hand, 11 core breeds were identified that were shared between the examined models and demonstrated more adequate clustering and admixture patterns. These findings will lay the foundation for future research to improve methods for clustering as well as genome- and phenome-wide association/mediation analyses.
Parental personality and early life ecology: a prospective cohort study from preconception to postpartum
Authors: Spry Elizabeth A. , Olsson Craig A. , Aarsman Stephanie R. , Mohamad Husin Hanafi , Macdonald Jacqui A. , Dashti S. Ghazaleh , Moreno-Betancur Margarita , Letcher Primrose , Biden Ebony J. , Thomson Kimberly C. , McAnally Helena , Greenwood Christopher J. , Middleton Melissa , Hutchinson Delyse M. , Carlin John B. , Patton George C. 
Published: February 2023

AbstractPersonality reliably predicts life outcomes ranging from social and material resources to mental health and interpersonal capacities. However, little is known about the potential intergenerational impact of parent personality prior to offspring conception on family resources and child development across the first thousand days of life. We analysed data from the Victorian Intergenerational Health Cohort Study (665 parents, 1030 infants; est. 1992), a two-generation study with prospective assessment of preconception background factors in parental adolescence, preconception personality traits in young adulthood (agreeableness, conscientiousness, emotional stability, extraversion, and openness), and multiple parental resources and infant characteristics in pregnancy and after the birth of their child. After adjusting for pre-exposure confounders, both maternal and paternal preconception personality traits were associated with numerous parental resources and attributes in pregnancy and postpartum, as well as with infant biobehavioural characteristics. Effect sizes ranged from small to moderate when considering parent personality traits as continuous exposures, and from small to large when considering personality traits as binary exposures. Young adult personality, well before offspring conception, is associated with the perinatal household social and financial context, parental mental health, parenting style and self-efficacy, and temperamental characteristics of offspring. These are pivotal aspects of early life development that ultimately predict a child’s long-term health and development.