bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunoproteasome-specific subunit PSMB9 induction is required to regulate cellular proteostasis upon mitochondrial dysfunction
Authors: Kim Minji , Serwa Remigiusz A. , Samluk Lukasz , Suppanz Ida , Kodroń Agata , Stępkowski Tomasz M. , Elancheliyan Praveenraj , Tsegaye Biniyam , Oeljeklaus Silke , Wasilewski Michal , Warscheid Bettina , Chacinska Agnieszka 
Published: July 2023

AbstractPerturbed cellular protein homeostasis (proteostasis) and mitochondrial dysfunction play an important role in neurodegenerative diseases, however, the interplay between these two phenomena remains unclear. Mitochondrial dysfunction leads to a delay in mitochondrial protein import, causing accumulation of non-imported mitochondrial proteins in the cytosol and challenging proteostasis. Cells respond by increasing proteasome activity and molecular chaperones in yeast andC. elegans. Here, we demonstrate that in human cells mitochondrial dysfunction leads to the upregulation of a chaperone HSPB1 and, interestingly, an immunoproteasome-specific subunit PSMB9. Moreover, PSMB9 expression is dependent on the translation elongation factor EEF1A2. These mechanisms constitute a defense response to preserve cellular proteostasis under mitochondrial stress. Our findings define a mode of proteasomal activation through the change in proteasome composition driven by EEF1A2 and its spatial regulation, and are useful to formulate therapies to prevent neurodegenerative diseases.
Active self-assembly of piezoelectric biomolecular films via synergistic nanoconfinement and in-situ poling
Authors: Zhang Zhuomin , Li Xuemu , Peng Zehua , Yan Xiaodong , Liu Shiyuan , Hong Ying , Shan Yao , Xu Xiaote , Jin Lihan , Liu Bingren , Zhang Xinyu , Chai Yu , Zhang Shujun , Jen Alex K.-Y. , Yang Zhengbao 
Published: July 2023

AbstractPiezoelectric biomaterials have attracted great attention owing to the recent recognition of the impact of piezoelectricity on biological systems and their potential applications in implantable sensors, actuators, and energy harvesters. However, their practical use is hindered by the weak piezoelectric effect caused by the random polarization of biomaterials and the challenges of large-scale alignment of domains. Here, we present an active self-assembly strategy to tailor piezoelectric biomaterial thin films. The nanoconfinement-induced homogeneous nucleation overcomes the interfacial dependency and allows the electric field applied in-situ to align crystal grains across the entire film. The β-glycine films exhibit an enhanced piezoelectric strain coefficient of 11.2 pm V−1 and an exceptional piezoelectric voltage coefficient of 252 × 10−3 Vm N−1. Of particular significance is that the nanoconfinement effect greatly improves the thermostability before melting (192 °C). This finding offers a generally applicable strategy for constructing high-performance large-sized piezoelectric bio-organic materials for biological and medical microdevices.
Interventional hydrogel microsphere vaccine as an immune amplifier for activated antitumour immunity after ablation therapy
Authors: Liu Xiaoyu , Zhuang Yaping , Huang Wei , Wu Zhuozhuo , Chen Yingjie , Shan Qungang , Zhang Yuefang , Wu Zhiyuan , Ding Xiaoyi , Qiu Zilong , Cui Wenguo , Wang Zhongmin 
Published: July 2023

AbstractThe response rate of pancreatic cancer to chemotherapy or immunotherapy pancreatic cancer is low. Although minimally invasive irreversible electroporation (IRE) ablation is a promising option for irresectable pancreatic cancers, the immunosuppressive tumour microenvironment that characterizes this tumour type enables tumour recurrence. Thus, strengthening endogenous adaptive antitumour immunity is critical for improving the outcome of ablation therapy and post-ablation immune therapy. Here we present a hydrogel microsphere vaccine that amplifies post-ablation anti-cancer immune response via releasing its cargo of FLT3L and CD40L at the relatively lower pH of the tumour bed. The vaccine facilitates migration of the tumour-resident type 1 conventional dendritic cells (cDC1) to the tumour-draining lymph nodes (TdLN), thus initiating the cDC1-mediated antigen cross-presentation cascade, resulting in enhanced endogenous CD8+ T cell response. We show in an orthotopic pancreatic cancer model in male mice that the hydrogel microsphere vaccine transforms the immunologically cold tumour microenvironment into hot in a safe and efficient manner, thus significantly increasing survival and inhibiting the growth of distant metastases.
An RNA modification enzyme directly senses reactive oxygen species for translational regulation in Enterococcus faecalis
Authors: Lee Wei Lin , Sinha Ameya , Lam Ling Ning , Loo Hooi Linn , Liang Jiaqi , Ho Peiying , Cui Liang , Chan Cheryl Siew Choo , Begley Thomas , Kline Kimberly Ann , Dedon Peter 
Published: July 2023

AbstractBacteria possess elaborate systems to manage reactive oxygen and nitrogen species (ROS) arising from exposure to the mammalian immune system and environmental stresses. Here we report the discovery of an ROS-sensing RNA-modifying enzyme that regulates translation of stress-response proteins in the gut commensal and opportunistic pathogen Enterococcus faecalis. We analyze the tRNA epitranscriptome of E. faecalis in response to reactive oxygen species (ROS) or sublethal doses of ROS-inducing antibiotics and identify large decreases in N2-methyladenosine (m2A) in both 23 S ribosomal RNA and transfer RNA. This we determine to be due to ROS-mediated inactivation of the Fe-S cluster-containing methyltransferase, RlmN. Genetic knockout of RlmN gives rise to a proteome that mimics the oxidative stress response, with an increase in levels of superoxide dismutase and decrease in virulence proteins. While tRNA modifications were established to be dynamic for fine-tuning translation, here we report the discovery of a dynamically regulated, environmentally responsive rRNA modification. These studies lead to a model in which RlmN serves as a redox-sensitive molecular switch, directly relaying oxidative stress to modulating translation through the rRNA and the tRNA epitranscriptome, adding a different paradigm in which RNA modifications can directly regulate the proteome.
Structural basis of CXC chemokine receptor 1 ligand binding and activation
Authors: Ishimoto Naito , Park Jae-Hyun , Kawakami Kouki , Tajiri Michiko , Mizutani Kenji , Akashi Satoko , Tame Jeremy R. H. , Inoue Asuka , Park Sam-Yong 
Published: July 2023

AbstractNeutrophil granulocytes play key roles in innate immunity and shaping adaptive immune responses. They are attracted by chemokines to sites of infection and tissue damage, where they kill and phagocytose bacteria. The chemokine CXCL8 (also known as interleukin-8, abbreviated IL-8) and its G-protein-coupled receptors CXCR1 and CXCR2 are crucial elements in this process, and also the development of many cancers. These GPCRs have therefore been the target of many drug development campaigns and structural studies. Here, we solve the structure of CXCR1 complexed with CXCL8 and cognate G-proteins using cryo-EM, showing the detailed interactions between the receptor, the chemokine and Gαi protein. Unlike the closely related CXCR2, CXCR1 strongly prefers to bind CXCL8 in its monomeric form. The model shows that steric clashes would form between dimeric CXCL8 and extracellular loop 2 (ECL2) of CXCR1. Consistently, transplanting ECL2 of CXCR2 onto CXCR1 abolishes the selectivity for the monomeric chemokine. Our model and functional analysis of various CXCR1 mutants will assist efforts in structure-based drug design targeting specific CXC chemokine receptor subtypes.
Carbene-stabilized enantiopure heterometallic clusters featuring EQE of 20.8% in circularly-polarized OLED
Authors: Ma Xiao-Hong , Li Jing , Luo Peng , Hu Jia-Hua , Han Zhen , Dong Xi-Yan , Xie Guohua , Zang Shuang-Quan 
Published: July 2023

AbstractBright and efficient chiral coinage metal clusters show promise for use in emerging circularly polarized light-emitting materials and diodes. To date, highly efficient circularly polarized organic light-emitting diodes (CP-OLEDs) with enantiopure metal clusters have not been reported. Herein, through rational design of a multidentate chiral N-heterocyclic carbene (NHC) ligand and a modular building strategy, we synthesize a series of enantiopure Au(I)-Cu(I) clusters with exceptional stability. Modulation of the ligands stabilize the chiral excited states of clusters to allow thermally activated delayed fluorescence, resulting in the highest orange-red photoluminescence quantum yields over 93.0% in the solid state, which is accompanied by circularly polarized luminescence. Based on the solution process, a prototypical orange-red CP-OLED with a considerably high external quantum efficiency of 20.8% is prepared. These results demonstrate the extensive designability of chiral NHC ligands to stabilize polymetallic clusters for high performance in chiroptical applications.
Increased precipitation over land due to climate feedback of large-scale bioenergy cultivation
Authors: Li Zhao , Ciais Philippe , Wright Jonathon S. , Wang Yong , Liu Shu , Wang Jingmeng , Li Laurent Z. X. , Lu Hui , Huang Xiaomeng , Zhu Lei , Goll Daniel S. , Li Wei 
Published: July 2023

AbstractBioenergy with carbon capture and storage (BECCS) is considered to be a key technology for removing carbon dioxide from the atmosphere. However, large-scale bioenergy crop cultivation results in land cover changes and activates biophysical effects on climate, with earth’s water recycling altered and energy budget re-adjusted. Here, we use a coupled atmosphere-land model with explicit representations of high-transpiration woody (i.e., eucalypt) and low-transpiration herbaceous (i.e., switchgrass) bioenergy crops to investigate the range of impact of large-scale rainfed bioenergy crop cultivation on the global water cycle and atmospheric water recycling. We find that global land precipitation increases under BECCS scenarios, due to enhanced evapotranspiration and inland moisture advection. Despite enhanced evapotranspiration, soil moisture decreases only slightly, due to increased precipitation and reduced runoff. Our results indicate that, at the global scale, the water consumption by bioenergy crop growth would be partially compensated by atmospheric feedbacks. Thus, to support more effective climate mitigation policies, a more comprehensive assessment, including the biophysical effects of bioenergy cultivation, is highly recommended.
High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors
Authors: Shiau Cheng-Kai , Lu Lina , Kieser Rachel , Fukumura Kazutaka , Pan Timothy , Lin Hsiao-Yun , Yang Jie , Tong Eric L. , Lee GaHyun , Yan Yuanqing , Huse Jason T. , Gao Ruli 
Published: July 2023

AbstractSingle-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies.
Temperature-pressure phase diagram of confined monolayer water/ice at first-principles accuracy with a machine-learning force field
Authors: Lin Bo , Jiang Jian , Zeng Xiao Cheng , Li Lei 
Published: July 2023

AbstractUnderstanding the phase behaviour of nanoconfined water films is of fundamental importance in broad fields of science and engineering. However, the phase behaviour of the thinnest water film – monolayer water – is still incompletely known. Here, we developed a machine-learning force field (MLFF) at first-principles accuracy to determine the phase diagram of monolayer water/ice in nanoconfinement with hydrophobic walls. We observed the spontaneous formation of two previously unreported high-density ices, namely, zigzag quasi-bilayer ice (ZZ-qBI) and branched-zigzag quasi-bilayer ice (bZZ-qBI). Unlike conventional bilayer ices, few inter-layer hydrogen bonds were observed in both quasi-bilayer ices. Notably, the bZZ-qBI entails a unique hydrogen-bonding network that consists of two distinctive types of hydrogen bonds. Moreover, we identified, for the first time, the stable region for the lowest-density $$4\cdot {8}^{2}$$
4
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8

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monolayer ice (LD-48MI) at negative pressures (<−0.3 GPa). Overall, the MLFF enables large-scale first-principle-level molecular dynamics (MD) simulations of the spontaneous transition from the liquid water to a plethora of monolayer ices, including hexagonal, pentagonal, square, zigzag (ZZMI), and hexatic monolayer ices. These findings will enrich our understanding of the phase behaviour of the nanoconfined water/ices and provide a guide for future experimental realization of the 2D ices.
polyBERT: a chemical language model to enable fully machine-driven ultrafast polymer informatics
Authors: Kuenneth Christopher , Ramprasad Rampi 
Published: July 2023

AbstractPolymers are a vital part of everyday life. Their chemical universe is so large that it presents unprecedented opportunities as well as significant challenges to identify suitable application-specific candidates. We present a complete end-to-end machine-driven polymer informatics pipeline that can search this space for suitable candidates at unprecedented speed and accuracy. This pipeline includes a polymer chemical fingerprinting capability called polyBERT (inspired by Natural Language Processing concepts), and a multitask learning approach that maps the polyBERT fingerprints to a host of properties. polyBERT is a chemical linguist that treats the chemical structure of polymers as a chemical language. The present approach outstrips the best presently available concepts for polymer property prediction based on handcrafted fingerprint schemes in speed by two orders of magnitude while preserving accuracy, thus making it a strong candidate for deployment in scalable architectures including cloud infrastructures.
Predicting scale-dependent chromatin polymer properties from systematic coarse-graining
Authors: Kadam Sangram , Kumari Kiran , Manivannan Vinoth , Dutta Shuvadip , Mitra Mithun K. , Padinhateeri Ranjith 
Published: July 2023

AbstractSimulating chromatin is crucial for predicting genome organization and dynamics. Although coarse-grained bead-spring polymer models are commonly used to describe chromatin, the relevant bead dimensions, elastic properties, and the nature of inter-bead potentials are unknown. Using nucleosome-resolution contact probability (Micro-C) data, we systematically coarse-grain chromatin and predict quantities essential for polymer representation of chromatin. We compute size distributions of chromatin beads for different coarse-graining scales, quantify fluctuations and distributions of bond lengths between neighboring regions, and derive effective spring constant values. Unlike the prevalent notion, our findings argue that coarse-grained chromatin beads must be considered as soft particles that can overlap, and we derive an effective inter-bead soft potential and quantify an overlap parameter. We also compute angle distributions giving insights into intrinsic folding and local bendability of chromatin. While the nucleosome-linker DNA bond angle naturally emerges from our work, we show two populations of local structural states. The bead sizes, bond lengths, and bond angles show different mean behavior at Topologically Associating Domain (TAD) boundaries and TAD interiors. We integrate our findings into a coarse-grained polymer model and provide quantitative estimates of all model parameters, which can serve as a foundational basis for all future coarse-grained chromatin simulations.
The Sherpa hypothesis: Phenotype-Preserving Disordered Proteins stabilize the phenotypes of neurons and oligodendrocytes
Authors: Norris Vic , Oláh Judit , Krylov Sergey N. , Uversky Vladimir N. , Ovádi Judit 
Published: July 2023

AbstractIntrinsically disordered proteins (IDPs), which can interact with many partner proteins, are central to many physiological functions and to various pathologies that include neurodegeneration. Here, we introduce the Sherpa hypothesis, according to which a subset of stable IDPs that we term Phenotype-Preserving Disordered Proteins (PPDP) play a central role in protecting cell phenotypes from perturbations. To illustrate and test this hypothesis, we computer-simulate some salient features of how cells evolve and differentiate in the presence of either a single PPDP or two incompatible PPDPs. We relate this virtual experiment to the pathological interactions between two PPDPs, α-synuclein and Tubulin Polymerization Promoting Protein/p25, in neurodegenerative disorders. Finally, we discuss the implications of the Sherpa hypothesis for aptamer-based therapies of such disorders.
MetaFlux: Meta-learning global carbon fluxes from sparse spatiotemporal observations
Authors: Nathaniel Juan , Liu Jiangong , Gentine Pierre 
Published: July 2023

AbstractWe provide a global, long-term carbon flux dataset of gross primary production and ecosystem respiration generated using meta-learning, calledMetaFlux. The idea behind meta-learning stems from the need to learn efficiently given sparse data by learning how to learn broad features across tasks to better infer other poorly sampled ones. Using meta-trained ensemble of deep models, we generate global carbon products on daily and monthly timescales at a 0.25-degree spatial resolution from 2001 to 2021, through a combination of reanalysis and remote-sensing products. Site-level validation finds that MetaFlux ensembles have lower validation error by 5–7% compared to their non-meta-trained counterparts. In addition, they are more robust to extreme observations, with 4–24% lower errors. We also checked for seasonality, interannual variability, and correlation to solar-induced fluorescence of the upscaled product and found that MetaFlux outperformed other machine-learning based carbon product, especially in the tropics and semi-arids by 10–40%. Overall, MetaFlux can be used to study a wide range of biogeochemical processes.
Transgenerational and intergenerational effects of early childhood famine exposure in the cohort of offspring of Leningrad Siege survivors
Authors: Tolkunova Kristina , Usoltsev Dmitrii , Moguchaia Ekaterina , Boyarinova Maria , Kolesova Ekaterina , Erina Anastasia , Voortman Trudy , Vasilyeva Elena , Kostareva Anna , Shlyakhto Evgeny , Konradi Alexandra , Rotar Oxana , Artomov Mykyta 
Published: July 2023

AbstractFamine exposure during early life development can affect disease risk in late-life period, yet, transmission of phenotypic features from famine-exposed individuals to the next generations has not been well characterized. The purpose of our case–control study was to investigate the association of parental starvation in the perinatal period and the period of early childhood with the phenotypic features observed in two generations of descendants of Leningrad siege survivors. We examined 54 children and 30 grandchildren of 58 besieged Leningrad residents who suffered from starvation in early childhood and prenatal age during the Second World War. Controls from the population-based national epidemiological ESSE-RF study (n = 175) were matched on sex, age and body mass index (BMI). Phenotypes of controls and descendants (both generations, children and grandchildren separately) were compared, taking into account multiple testing. Comparison of two generations descendants with corresponding control groups revealed significantly higher creatinine and lower glomerular filtration rate (GFR), both in meta-analysis and in independent analyses. The mean values of GFR for all groups were within the normal range (GFR less than 60 mL/min/1.73 m2 was recorded in 2 controls and no one in DLSS). Additionally, independent of the creatinine level, differences in the eating pattern were detected: insufficient fish and excessive red meat consumption were significantly more frequent in the children of the Leningrad siege survivors compared with controls. Blood pressure, blood lipids and glucose did not differ between the groups. Parental famine exposure in early childhood may contribute to a decrease in kidney filtration capacity and altered eating pattern in the offspring of famine-exposed individuals.
Multimodal multitask learning for predicting MCI to AD conversion using stacked polynomial attention network and adaptive exponential decay
Authors: Ho Ngoc-Huynh , Jeong Yang-Hyung , Kim Jahae 
Published: July 2023

AbstractEarly identification and treatment of moderate cognitive impairment (MCI) can halt or postpone Alzheimer’s disease (AD) and preserve brain function. For prompt diagnosis and AD reversal, precise prediction in the early and late phases of MCI is essential. This research investigates multimodal framework-based multitask learning in the following situations: (1) Differentiating early mild cognitive impairment (eMCI) from late MCI and (2) predicting when an MCI patient would acquire AD. Clinical data and two radiomics features on three brain areas deduced from magnetic resonance imaging were investigated (MRI). We proposed an attention-based module, Stack Polynomial Attention Network (SPAN), to firmly encode clinical and radiomics data input characteristics for successful representation from a small dataset. To improve multimodal data learning, we computed a potent factor using adaptive exponential decay (AED). We used experiments from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort study, which included 249 eMCI and 427 lMCI participants at baseline visits. The proposed multimodal strategy yielded the best c-index score in time prediction of MCI to AD conversion (0.85) and the best accuracy in MCI-stage categorization ($$83.19\%$$83.19%). Moreover, our performance was equivalent to that of contemporary research.