bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emerging roles of ferroptosis-related miRNAs in tumor metastasis
Authors: Jiang Zhongyi , Zhou Jing , Deng Junqi , Li Luohong , Wang Ruifeng , Han Yingying , Zhou Junyu , Tao Rui , Peng Lushan , Wang Dan , Huang Tao , Yu Yupei , Zhou Zongjiang , Li Jinghe , Ousmane Diabate , Wang Junpu 
Published: June 2023

AbstractFerroptosis, a novel mode of cell death dependent on iron and reactive oxygen species, has been extensively explored during malignant tumors metastasis. Ferroptosis can interact with multiple components of the tumor microenvironment to regulate metastasis. These interactions generally include the following aspects: (1) Epithelial-mesenchymal transformation, which can help cancer cells increase their sensitivity to ferroptosis while they have multiple mechanisms to fight against it; (2) Disorder of iron metabolism in cancer stem cells which maintains their stem characteristics; (3) Polarization of M0 macrophages to M2. (4) The paradoxical effects of iron metabolism and CD8 + T cells induced by ferroptosis (5) Regulation of angiogenesis. In addition, ferroptosis can be regulated by miRNAs through the reprogramming of various intracellular metabolism processes, including the regulation of the glutathione- glutathione peroxidase 4 pathway, glutamic acid/cystine transport, iron metabolism, lipid metabolism, and oxidative stress. Therefore, there are many potential interactions between ferroptosis-related miRNAs and tumor metastasis, including interaction with cancer cells and immune cells, regulating cytokines, and angiogenesis. This review focuses on the role of ferroptosis-related miRNA in tumor metastasis, aiming to help readers understand their relationship and provide a new perspective on the potential treatment strategies of malignant tumors.
SNORD6 promotes cervical cancer progression by accelerating E6-mediated p53 degradation
Authors: Li Qianhui , Xie Bumin , Chen Xi , Lu Bingfeng , Chen Shuo , Sheng Xiujie , Zhao Yang 
Published: June 2023

AbstractSmall nucleolar RNAs (snoRNAs) are a class of non-coding RNAs widely distributed in eukaryotic nucleoli. In recent years, studies have revealed that snoRNAs can also participate in the occurrence and development of malignant tumors through different pathways. Cervical cancer is one of the most common malignant tumors of the female reproductive system, and the high-risk HPV virus infection is its main pathogenic mechanism. However, the outcomes in different patients with malignant tumors vary, indicating that other factors might affect the pathogenic process of cervical cancer. In this study, we screened the poor prognosis indicator SNORD6 from the TCGA database to find the snoRNA that affects the disease outcome during the pathogenesis of cervical cancer. We discovered that SNORD6 expression in cervical cancer tissues was higher than that in normal cervical tissues. Cell phenotype experiments revealed that the knockdown of SNORD6 retarded cell proliferation and plate clone formation. Furthermore, G1-S phase cell cycle arrest was induced, DNA synthesis was decreased, cell migration and invasion were reduced, while the level of apoptosis increased, whereas the opposite results were obtained after SNORD6 overexpression. Moreover, after intratumoral injection of ASO-SNORD6, the tumor growth rate slowed down, and the tumor volume decreased compared with the control group. In the mechanism study, we found that SNORD6 concurrently acted as a binding “hub” to promote the formation of the tumor suppressor protein p53 degradation complex E6-E6AP-p53. This reaction enhanced the ubiquitination and degradation of p53, thus influenced the regulation of p53 activities in the cell cycle and apoptosis. This study preliminarily clarified the biological role and specific mechanism of SNORD6 in the occurrence of cervical cancer, broadening the basic theoretical research of ovarian cancer and may provide a new perspective on the diagnosis and treatment of cervical cancer.
Age-associated B cells predict impaired humoral immunity after COVID-19 vaccination in patients receiving immune checkpoint blockade
Authors: Yam-Puc Juan Carlos , Hosseini Zhaleh , Horner Emily C. , Gerber Pehuén Pereyra , Beristain-Covarrubias Nonantzin , Hughes Robert , Lulla Aleksei , Rust Maria , Boston Rebecca , Ali Magda , Fischer Katrin , Simmons-Rosello Edward , O’Reilly Martin , Robson Harry , Booth Lucy H. , Kahanawita Lakmini , Correa-Noguera Andrea , Favara David , Ceron-Gutierrez Lourdes , Keller Baerbel , Craxton Andrew , Anderson Georgina S. F. , Sun Xiao-Ming , Elmer Anne , Saunders Caroline , Bermperi Areti , Jose Sherly , Kingston Nathalie , Mulroney Thomas E. , Piñon Lucia P. G. ,   CITIID-NIHR COVID−19 BioResource Collaboration, Chapman Michael A. , Grigoriadou Sofia , MacFarlane Marion , Willis Anne E. , Patil Kiran R. , Spencer Sarah , Staples Emily , Warnatz Klaus , Buckland Matthew S. , Hollfelder Florian , Hyvönen Marko , Döffinger Rainer , Parkinson Christine , Lear Sara , Matheson Nicholas J. , Thaventhiran James E. D. 
Published: June 2023

AbstractAge-associated B cells (ABC) accumulate with age and in individuals with different immunological disorders, including cancer patients treated with immune checkpoint blockade and those with inborn errors of immunity. Here, we investigate whether ABCs from different conditions are similar and how they impact the longitudinal level of the COVID-19 vaccine response. Single-cell RNA sequencing indicates that ABCs with distinct aetiologies have common transcriptional profiles and can be categorised according to their expression of immune genes, such as the autoimmune regulator (AIRE). Furthermore, higher baseline ABC frequency correlates with decreased levels of antigen-specific memory B cells and reduced neutralising capacity against SARS-CoV-2. ABCs express high levels of the inhibitory FcγRIIB receptor and are distinctive in their ability to bind immune complexes, which could contribute to diminish vaccine responses either directly, or indirectly via enhanced clearance of immune complexed-antigen. Expansion of ABCs may, therefore, serve as a biomarker identifying individuals at risk of suboptimal responses to vaccination.
Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor
Authors: Gligorovski Vojislav , Sadeghi Ahmad , Rahi Sahand Jamal 
Published: June 2023

AbstractThe ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z3EV, blue-light inducible optogenetic systems El222-LIP, El222-GLIP, and red-light inducible PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of each system using an intuitive unit, maxGAL1. We uncover disadvantages of widely used tools, e.g., nonmonotonic activity of MET3pr and GALL, slow off kinetics of the doxycycline- and estradiol-inducible systems tetOpr and Z3EV, and high variability of PHO5pr and red-light activated PhyB-PIF3 system. We introduce two previously uncharacterized systems: strongLOV, a more light-sensitive El222 mutant, and ARG3pr, which is induced in the absence of arginine or presence of methionine. To demonstrate fine control over gene circuits, we experimentally tune the time between cell cycle Start and mitosis, artificially simulating near-wild-type timing. All strains, constructs, code, and data (https://promoter-benchmark.epfl.ch/) are made available.
Interspecies exciton interactions lead to enhanced nonlinearity of dipolar excitons and polaritons in MoS2 homobilayers
Authors: Louca Charalambos , Genco Armando , Chiavazzo Salvatore , Lyons Thomas P. , Randerson Sam , Trovatello Chiara , Claronino Peter , Jayaprakash Rahul , Hu Xuerong , Howarth James , Watanabe Kenji , Taniguchi Takashi , Dal Conte Stefano , Gorbachev Roman , Lidzey David G. , Cerullo Giulio , Kyriienko Oleksandr , Tartakovskii Alexander I. 
Published: June 2023

AbstractNonlinear interactions between excitons strongly coupled to light are key for accessing quantum many-body phenomena in polariton systems. Atomically-thin two-dimensional semiconductors provide an attractive platform for strong light-matter coupling owing to many controllable excitonic degrees of freedom. Among these, the recently emerged exciton hybridization opens access to unexplored excitonic species, with a promise of enhanced interactions. Here, we employ hybridized interlayer excitons (hIX) in bilayer MoS2 to achieve highly nonlinear excitonic and polaritonic effects. Such interlayer excitons possess an out-of-plane electric dipole as well as an unusually large oscillator strength allowing observation of dipolar polaritons (dipolaritons) in bilayers in optical microcavities. Compared to excitons and polaritons in MoS2 monolayers, both hIX and dipolaritons exhibit ≈ 8 times higher nonlinearity, which is further strongly enhanced when hIX and intralayer excitons, sharing the same valence band, are excited simultaneously. This provides access to an unusual nonlinear regime which we describe theoretically as a mixed effect of Pauli exclusion and exciton-exciton interactions enabled through charge tunnelling. The presented insight into many-body interactions provides new tools for accessing few-polariton quantum correlations.
A unique van Hove singularity in kagome superconductor CsV3-xTaxSb5 with enhanced superconductivity
Authors: Luo Yang , Han Yulei , Liu Jinjin , Chen Hui , Huang Zihao , Huai Linwei , Li Hongyu , Wang Bingqian , Shen Jianchang , Ding Shuhan , Li Zeyu , Peng Shuting , Wei Zhiyuan , Miao Yu , Sun Xiupeng , Ou Zhipeng , Xiang Ziji , Hashimoto Makoto , Lu Donghui , Yao Yugui , Yang Haitao , Chen Xianhui , Gao Hong-Jun , Qiao Zhenhua , Wang Zhiwei , He Junfeng 
Published: June 2023

AbstractVan Hove singularity (VHS) has been considered as a driving source for unconventional superconductivity. A VHS in two-dimensional (2D) materials consists of a saddle point connecting electron-like and hole-like bands. In a rare case, when a VHS appears at Fermi level, both electron-like and hole-like conduction can coexist, giving rise to an enhanced density of states as well as an attractive component of Coulomb interaction for unconventional electronic pairing. However, this van Hove scenario is often destroyed by an incorrect chemical potential or competing instabilities. Here, by using angle-resolved photoemission measurements, we report the observation of a VHS perfectly aligned with the Fermi level in a kagome superconductor CsV3-xTaxSb5 (x ~ 0.4), in which a record-high superconducting transition temperature is achieved among all the current variants of AV3Sb5 (A = Cs, Rb, K) at ambient pressure. Doping dependent measurements reveal the important role of van Hove scenario in boosting superconductivity, and spectroscopic-imaging scanning tunneling microscopy measurements indicate a distinct superconducting state in this system.
T cell infiltration into the brain triggers pulmonary dysfunction in murine Cryptococcus-associated IRIS
Authors: Kawano Tasuku , Zhou Jinyan , Anwar Shehata , Salah Haneen , Dayal Andrea H. , Ishikawa Yuzuki , Boetel Katelyn , Takahashi Tomoko , Sharma Kamal , Inoue Makoto 
Published: June 2023

AbstractCryptococcus-associated immune reconstitution inflammatory syndrome (C-IRIS) is a condition frequently occurring in immunocompromised patients receiving antiretroviral therapy. C-IRIS patients exhibit many critical symptoms, including pulmonary distress, potentially complicating the progression and recovery from this condition. Here, utilizing our previously established mouse model of unmasking C-IRIS (CnH99 preinfection and adoptive transfer of CD4+T cells), we demonstrated that pulmonary dysfunction associated with the C-IRIS condition in mice could be attributed to the infiltration of CD4+T cells into the brain via the CCL8-CCR5 axis, which triggers the nucleus tractus solitarius (NTS) neuronal damage and neuronal disconnection via upregulated ephrin B3 and semaphorin 6B in CD4+T cells. Our findings provide unique insight into the mechanism behind pulmonary dysfunction in C-IRIS and nominate potential therapeutic targets for treatment.
A landscape of response to drug combinations in non-small cell lung cancer
Authors: Nair Nishanth Ulhas , Greninger Patricia , Zhang Xiaohu , Friedman Adam A. , Amzallag Arnaud , Cortez Eliane , Sahu Avinash Das , Lee Joo Sang , Dastur Anahita , Egan Regina K. , Murchie Ellen , Ceribelli Michele , Crowther Giovanna S. , Beck Erin , McClanaghan Joseph , Klump-Thomas Carleen , Boisvert Jessica L. , Damon Leah J. , Wilson Kelli M. , Ho Jeffrey , Tam Angela , McKnight Crystal , Michael Sam , Itkin Zina , Garnett Mathew J. , Engelman Jeffrey A. , Haber Daniel A. , Thomas Craig J. , Ruppin Eytan , Benes Cyril H. 
Published: June 2023

AbstractCombination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction.
Predicting electronic structures at any length scale with machine learning
Authors: Fiedler Lenz , Modine Normand A. , Schmerler Steve , Vogel Dayton J. , Popoola Gabriel A. , Thompson Aidan P. , Rajamanickam Sivasankaran , Cangi Attila 
Published: June 2023

AbstractThe properties of electrons in matter are of fundamental importance. They give rise to virtually all material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant gas planets. Modeling and simulation of such diverse applications rely primarily on density functional theory (DFT), which has become the principal method for predicting the electronic structure of matter. While DFT calculations have proven to be very useful, their computational scaling limits them to small systems. We have developed a machine learning framework for predicting the electronic structure on any length scale. It shows up to three orders of magnitude speedup on systems where DFT is tractable and, more importantly, enables predictions on scales where DFT calculations are infeasible. Our work demonstrates how machine learning circumvents a long-standing computational bottleneck and advances materials science to frontiers intractable with any current solutions.
Signing data citations enables data verification and citation persistence
Authors: Elliott Michael J. , Poelen Jorrit H. , Fortes José A. B. 
Published: June 2023

AbstractCommonly used data citation practices rely on unverifiable retrieval methods which are susceptible to content drift, which occurs when the data associated with an identifier have been allowed to change. Based on our earlier work on reliable dataset identifiers, we propose signed citations, i.e., customary data citations extended to also include a standards-based, verifiable, unique, and fixed-length digital content signature. We show that content signatures enable independent verification of the cited content and can improve the persistence of the citation. Because content signatures are location- and storage-medium-agnostic, cited data can be copied to new locations to ensure their persistence across current and future storage media and data networks. As a result, content signatures can be leveraged to help scalably store, locate, access, and independently verify content across new and existing data infrastructures. Content signatures can also be embedded inside content to create robust, distributed knowledge graphs that can be cited using a single signed citation. We describe applications of signed citations to solve real-world data collection, identification, and citation challenges.
An open dataset for intelligent recognition and classification of abnormal condition in longwall mining
Authors: Yang Wenjuan , Zhang Xuhui , Ma Bing , Wang Yanqun , Wu Yujia , Yan Jianxing , Liu Yongwei , Zhang Chao , Wan Jicheng , Wang Yue , Huang Mengyao , Li Yuyang , Zhao Dian 
Published: June 2023

AbstractThe underground coal mine production of the fully mechanized mining face exists many problems, such as poor operating environment, high accident rate and so on. Recently, the intelligent autonomous coal mining is gradually replacing the traditional mining process. The artificial intelligence technology is an active research area and is expect to identify and warn the underground abnormal conditions for intelligent longwall mining. It is inseparable from the construction of datasets, but the downhole dataset is still blank at present. This work develops an image dataset of underground longwall mining face (DsLMF+), which consists of 138004 images with annotation 6 categories of mine personnel, hydraulic support guard plate, large coal, towline, miners’ behaviour and mine safety helmet. All the labels of dataset are publicly available in YOLO format and COCO format. The availability and accuracy of the datasets were reviewed by experts in coal mine field. The dataset is open access and aims to support further research and advancement of the intelligent identification and classification of abnormal conditions for underground mining.
Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease
Authors: Österdahl Marc F. , Whiston Ronan , Sudre Carole H. , Asnicar Francesco , Cheetham Nathan J. , Blanco Miguez Aitor , Bowyer Vicky , Antonelli Michela , Snell Olivia , dos Santos Canas Liane , Hu Christina , Wolf Jonathan , Menni Cristina , Malim Michael , Hart Deborah , Spector Tim , Berry Sarah , Segata Nicola , Doores Katie , Ourselin Sebastien , Duncan Emma L. , Steves Claire J. 
Published: June 2023

AbstractWhilst most individuals with SARS-CoV-2 infection have relatively mild disease, managed in the community, it was noted early in the pandemic that individuals with cardiovascular risk factors were more likely to experience severe acute disease, requiring hospitalisation. As the pandemic has progressed, increasing concern has also developed over long symptom duration in many individuals after SARS-CoV-2 infection, including among the majority who are managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. Here, we examine post-illness metabolomic profiles, using nuclear magnetic resonance (Nightingale Health Oyj), and gut-microbiome profiles, using shotgun metagenomic sequencing (Illumina Inc), in 2561 community-dwelling participants with SARS-CoV-2. Illness duration ranged from asymptomatic (n = 307) to Post-COVID Syndrome (n = 180), and included participants with prolonged non-COVID-19 illnesses (n = 287). We also assess a pre-established metabolomic biomarker score, previously associated with hospitalisation for both acute pneumonia and severe acute COVID-19 illness, for its association with illness duration. We found an atherogenic-dyslipidaemic metabolic profile, including biomarkers such as fatty acids and cholesterol, was associated with longer duration of illness, both in individuals with and without SARS-CoV-2 infection. Greater values of a pre-existing metabolomic biomarker score also associated with longer duration of illness, regardless of SARS-CoV-2 infection. We found no association between illness duration and gut microbiome profiles in convalescence. This highlights the potential role of cardiometabolic dysfunction in relation to the experience of long duration symptoms after symptoms of acute infection, both COVID-19 as well as other illnesses.
Suspended hydrogel culture as a method to scale up intestinal organoids
Authors: Co Julia Y. , Klein Jessica A. , Kang Serah , Homan Kimberly A. 
Published: June 2023

AbstractPrimary tissue-derived epithelial organoids are a physiologically relevant in vitro intestinal model that have been implemented for both basic research and drug development applications. The existing method of culturing intestinal organoids in surface-attached native extracellular matrix (ECM) hydrogel domes is not readily amenable to large-scale culture and contributes to culture heterogeneity. We have developed a method of culturing intestinal organoids within suspended basement membrane extract (BME) hydrogels of various geometries, which streamlines the protocol, increases the scalability, enables kinetic sampling, and improves culture uniformity without specialized equipment or additional expertise. We demonstrate the compatibility of this method with multiple culture formats, and provide examples of suspended BME hydrogel organoids in downstream applications: implementation in a medium-throughput drug screen and generation of Transwell monolayers for barrier evaluation. The suspended BME hydrogel culture method will allow intestinal organoids, and potentially other organoid types, to be used more widely and at higher throughputs than previously possible.