bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spectral characteristics of the black hole binary 4U 1957+115: a multi mission perspective
Authors: Mudambi S P , Gudennavar S B , Misra R , Bubbly S G 
Published: October 2022

ABSTRACT
We report spectral analysis of the persistent black hole X-ray binary, 4U 1957+115, using AstroSat, Swift, and NuSTAR observations carried out between 2016 and 2019. Modelling with a disc emission, thermal Comptonization, and blurred reflection components revealed that the source was in the high-soft state with the disc flux ∼87 per cent of the total and high-energy photon index ∼2.6. There is an evidence that either the inner disc radius varied by ∼25 per cent or the colour hardening factor changed by ∼12 per cent. The values of the inner disc radius imply that for a non-spinning black hole, the black hole mass is  &lt; 7 M ⊙ and the source is located  &gt; 30 kpc away. On the other hand, a rapidly spinning black hole would be consistent with the more plausible black hole mass of  &lt; 10 M ⊙ and a source distance of ∼10 kpc. Fixing the distance to 10 kpc and using a relativistic accretion disc model, constrained the black hole mass to 6 M⊙ and inclination angle to 72°. A positive correlation is detected between the accretion rate and inner radii or equivalently between the accretion rate and colour factor.
The burst mode of accretion in massive star formation with stellar inertia
Authors: Meyer D M-A , Vorobyov E I , Elbakyan V G , Kraus S , Liu S-Y , Nayakshin S , Sobolev A M 
Published: October 2022

ABSTRACT
The burst mode of accretion in massive star formation is a scenario linking the initial gravitational collapse of parent pre-stellar cores to the properties of their gravitationally unstable discs and of their accretion-driven bursts. In this study, we present a series of high-resolution 3D radiation-hydrodynamics numerical simulations for young massive stars formed out of collapsing $100{\rm M}_{\odot }$ molecular cores, spinning with several values of the ratio of rotational-to-gravitational energies $\beta =5{{-}9\ per cent}$. The models include the indirect gravitational potential caused by disc asymmetries. We find that this modifies the barycentre of the disc, causing significant excursions of the central star position, which we term stellar wobbling. The stellar wobbling slows down and protracts the development of gravitational instability in the disc, reducing the number and magnitude of the accretion-driven bursts undergone by the young massive stars, whose properties are in good agreement with that of the burst monitored from the massive protostar M17 MIR. Including stellar wobbling is therefore important for accurate modelling disc structures. Synthetic alma interferometric images in the millimetre waveband show that the outcomes of efficient gravitational instability such as spiral arms and gaseous clumps can be detected for as long as the disc is old enough and has already entered the burst mode of accretion.
Machine-learning classification of astronomical sources: estimating F1-score in the absence of ground truth
Authors: Humphrey A , Kuberski W , Bialek J , Perrakis N , Cools W , Nuyttens N , Elakhrass H , Cunha P A C 
Published: October 2022

ABSTRACT
Machine-learning based classifiers have become indispensable in the field of astrophysics, allowing separation of astronomical sources into various classes, with computational efficiency suitable for application to the enormous data volumes that wide-area surveys now typically produce. In the standard supervised classification paradigm, a model is typically trained and validated using data from relatively small areas of sky, before being used to classify sources in other areas of the sky. However, population shifts between the training examples and the sources to be classified can lead to ‘silent’ degradation in model performance, which can be challenging to identify when the ground-truth is not available. In this letter, we present a novel methodology using the nannyml Confidence-Based Performance Estimation (CBPE) method to predict classifier F1-score in the presence of population shifts, but without ground-truth labels. We apply CBPE to the selection of quasars with decision-tree ensemble models, using broad-band photometry, and show that the F1-scores are predicted remarkably well (${\rm MAPE} \sim 10{{\ \rm per\ cent}}$; R2 = 0.74–0.92). We discuss potential use-cases in the domain of astronomy, including machine-learning model and/or hyperparameter selection, and evaluation of the suitability of training data sets for a particular classification problem.
The impact of two massive early accretion events in a Milky Way-like galaxy: repercussions for the buildup of the stellar disc and halo
Authors: Orkney Matthew D A , Laporte Chervin F P , Grand Robert J J , Gómez Facundo A , van de Voort Freeke , Marinacci Federico , Fragkoudi Francesca , Pakmor Ruediger , Springel Volker 
Published: October 2022

ABSTRACT
We identify and characterize a Milky Way-like realization from the Auriga simulations with two consecutive massive mergers $\sim 2$ Gyr apart at high redshift, comparable to the reported Kraken and Gaia-Sausage-Enceladus. The Kraken-like merger (z = 1.6, $M_{\rm Tot}=8\times 10^{10}\, \rm {M_{\odot }}$) is gas-rich, deposits most of its mass in the inner $10\,$ kpc, and is largely isotropic. The Sausage-like merger (z = 1.14, $M_{\rm Tot}=1\times 10^{11}\, \rm {M_{\odot }}$) leaves a more extended mass distribution at higher energies, and has a radially anisotropic distribution. For the higher-redshift merger, the stellar mass ratio of the satellite to host galaxy is high (1:3). As a result, the chemistry of the remnant is indistinguishable from contemporaneous in situ populations, making it challenging to identify through chemical abundances. This naturally explains why all abundance patterns attributed so far to Kraken are in fact fully consistent with the metal-poor in situ so-called Aurora population and thick disc. However, our model makes a falsifiable prediction: if the Milky Way underwent a gas-rich double merger at high redshift, then this should be imprinted on its star formation history with bursts about $\sim 2\,$ s apart. This may offer constraining power on the highest-redshift massive mergers.
DRESIS: the first comprehensive landscape of drug resistance information
Authors: Sun Xiuna , Zhang Yintao , Li Hanyang , Zhou Ying , Shi Shuiyang , Chen Zhen , He Xin , Zhang Hanyu , Li Fengcheng , Yin Jiayi , Mou Minjie , Wang Yunzhu , Qiu Yunqing , Zhu Feng 
Published: October 2022

Abstract
Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named ‘DRESIS’ was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/
DrugMAP: molecular atlas and pharma-information of all drugs
Authors: Li Fengcheng , Yin Jiayi , Lu Mingkun , Mou Minjie , Li Zhaorong , Zeng Zhenyu , Tan Ying , Wang Shanshan , Chu Xinyi , Dai Haibin , Hou Tingjun , Zeng Su , Chen Yuzong , Zhu Feng 
Published: October 2022

Abstract
The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for &gt;30 000 drugs/drug candidates, gives the differential expression patterns for &gt;5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing &gt;200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/
TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies
Authors: Lu Mingming , Zhang Yadong , Yang Fengchun , Mai Jialin , Gao Qianwen , Xu Xiaowei , Kang Hongyu , Hou Li , Shang Yunfei , Qain Qiheng , Liu Jie , Jiang Meiye , Zhang Hao , Bu Congfan , Wang Jinyue , Zhang Zhewen , Zhang Zaichao , Zeng Jingyao , Li Jiao , Xiao Jingfa 
Published: October 2022

Abstract
Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene–trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene–trait associations is constructed together with single nucleotide polymorphism (SNP)–gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.
USP15 promotes cGAS activation through deubiquitylation and liquid condensation
Authors: Shi Chengrui , Yang Xikang , Hou Yanfei , Jin Xue , Guo Lerui , Zhou Yi , Zhang Conggang , Yin Hang 
Published: October 2022

AbstractDouble-stranded DNA (dsDNA) is recognized as a danger signal by cyclic GMP-AMP synthase (cGAS), which triggers innate immune responses. cGAS activity must be properly regulated to maintain immune homeostasis. However, the mechanism by which cGAS activation is controlled remains to be better understood. In this study, we identified USP15 as a cGAS-interacting partner. USP15 promoted DNA-induced cGAS activation and downstream innate immune responses through a positive feedback mechanism. Specifically, USP15 deubiquitylated cGAS and promoted its activation. In the absence of DNA, USP15 drove cGAS dimerization and liquid condensation through the USP15 intrinsic disordered region (IDR), which prepared cGAS for a rapid response to DNA. Upon DNA stimulation, USP15 was induced to express and boost cGAS activation, functioning as an efficient amplifier in innate immune signal transduction. In summary, the positive role played by USP15-mediated cGAS activation may be a novel regulatory mechanism in the fine-tuning of innate immunity.
RABC: Rheumatoid Arthritis Bioinformatics Center
Authors: Chen Haiyan , Xu Jing , Wei Siyu , Jia Zhe , Sun Chen , Kang Jingxuan , Guo Xuying , Zhang Nan , Tao Junxian , Dong Yu , Zhang Chen , Ma Yingnan , Lv Wenhua , Tian Hongsheng , Bi Shuo , Lv Hongchao , Huang Chen , Kong Fanwu , Tang Guoping , Jiang Yongshuai , Zhang Mingming 
Published: October 2022

Abstract
Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.
Nature-inspired engineering of an artificial ligase enzyme by domain fusion
Authors: Tong Cher Ling , Kanwar Nisha , Morrone Dana J , Seelig Burckhard 
Published: October 2022

Abstract
The function of most proteins is accomplished through the interplay of two or more protein domains and fine-tuned by natural evolution. In contrast, artificial enzymes have often been engineered from a single domain scaffold and frequently have lower catalytic activity than natural enzymes. We previously generated an artificial enzyme that catalyzed an RNA ligation by &gt;2 million-fold but was likely limited in its activity by low substrate affinity. Inspired by nature's concept of domain fusion, we fused the artificial enzyme to a series of protein domains known to bind nucleic acids with the goal of improving its catalytic activity. The effect of the fused domains on catalytic activity varied greatly, yielding severalfold increases but also reductions caused by domains that previously enhanced nucleic acid binding in other protein engineering projects. The combination of the two better performing binding domains improved the activity of the parental ligase by more than an order of magnitude. These results demonstrate for the first time that nature's successful evolutionary mechanism of domain fusion can also improve an unevolved primordial-like protein whose structure and function had just been created in the test tube. The generation of multi-domain proteins might therefore be an ancient evolutionary process.
MeDBA: the Metalloenzyme Data Bank and Analysis platform
Authors: Yu Jun-Lin , Wu Song , Zhou Cong , Dai Qing-Qing , Schofield Christopher J , Li Guo-Bo 
Published: October 2022

AbstractMetalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.
Catastrophic chromosome fragmentation probes the nucleoid structure and dynamics in Escherichia coli
Authors: Mahaseth Tulip , Kuzminov Andrei 
Published: October 2022

Abstract
Escherichia coli cells treated with a combination of cyanide (CN) and hydrogen peroxide (HP) succumb to catastrophic chromosome fragmentation (CCF), detectable in pulsed-field gels as &gt;100 double-strand breaks per genome equivalent. Here we show that CN + HP-induced double-strand breaks are independent of replication and occur uniformly over the chromosome,—therefore we used CCF to probe the nucleoid structure by measuring DNA release from precipitated nucleoids. CCF releases surprisingly little chromosomal DNA from the nucleoid suggesting that: (i) the nucleoid is a single DNA-protein complex with only limited stretches of protein-free DNA and (ii) CN + HP-induced breaks happen within these unsecured DNA stretches, rather than at DNA attachments to the central scaffold. Mutants lacking individual nucleoid-associated proteins (NAPs) release more DNA during CCF, consistent with NAPs anchoring chromosome to the central scaffold (Dps also reduces the number of double-strand breaks directly). Finally, significantly more broken DNA is released once ATP production is restored, with about two-thirds of this ATP-dependent DNA release being due to transcription, suggesting that transcription complexes act as pulleys to move DNA loops. In addition to NAPs, recombinational repair of double-strand breaks also inhibits DNA release by CCF, contributing to a dynamic and complex nucleoid structure.
A sePARate phase? Poly(ADP-ribose) versus RNA in the organization of biomolecular condensates
Authors: Alemasova Elizaveta E , Lavrik Olga I 
Published: October 2022

Abstract
Condensates are biomolecular assemblies that concentrate biomolecules without the help of membranes. They are morphologically highly versatile and may emerge via distinct mechanisms. Nucleic acids–DNA, RNA and poly(ADP-ribose) (PAR) play special roles in the process of condensate organization. These polymeric scaffolds provide multiple specific and nonspecific interactions during nucleation and ‘development’ of macromolecular assemblages. In this review, we focus on condensates formed with PAR. We discuss to what extent the literature supports the phase separation origin of these structures. Special attention is paid to similarities and differences between PAR and RNA in the process of dynamic restructuring of condensates during their functioning.
G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation
Authors: Liu Xingyu , Cui Shuangyu , Qi Qianqian , Lei Huajun , Zhang Yutong , Shen Wei , Fu Fang , Tian Tian , Zhou Xiang 
Published: October 2022

Abstract
It is important to develop small moelcule-based methods to modulate gene editing and expression in human cells. The roles of the G-quadruplex (G4) in biological systems have been widely studied. Here, G4-guided RNA engineering is performed to generate guide RNA with G4-forming units (G4-gRNA). We further demonstrate that chemical targeting of G4-gRNAs holds promise as a general approach for modulating gene editing and expression in human cells. The rich structural diversity of RNAs offers a reservoir of targets for small molecules to bind, thus creating the potential to modulate RNA biology.
PertOrg 1.0: a comprehensive resource of multilevel alterations induced in model organisms by in vivo genetic perturbation
Authors: Zhai Zhaoyu , Zhang Xuelu , Zhou Lu , Lin Zhewei , Kuang Ni , Li Qiang , Ma Qinfeng , Tao Haodong , Gao Jieya , Ma Shiyong , Pan Jianbo 
Published: October 2022

Abstract
Genetically modified organisms (GMOs) can be generated to model human genetic disease or plant disease resistance, and they have contributed to the exploration and understanding of gene function, physiology, disease onset and drug target discovery. Here, PertOrg (http://www.inbirg.com/pertorg/) was introduced to provide multilevel alterations in GMOs. Raw data of 58 707 transcriptome profiles and associated information, such as phenotypic alterations, were collected and curated from studies involving in vivo genetic perturbation (e.g. knockdown, knockout and overexpression) in eight model organisms, including mouse, rat and zebrafish. The transcriptome profiles from before and after perturbation were organized into 10 116 comparison datasets, including 122 single-cell RNA-seq datasets. The raw data were checked and analysed using widely accepted and standardized pipelines to identify differentially expressed genes (DEGs) in perturbed organisms. As a result, 8 644 148 DEGs were identified and deposited as signatures of gene perturbations. Downstream functional enrichment analysis, cell type analysis and phenotypic alterations were also provided when available. Multiple search methods and analytical tools were created and implemented. Furthermore, case studies were presented to demonstrate how users can utilize the database. PertOrg 1.0 will be a valuable resource aiding in the exploration of gene functions, biological processes and disease models.
HProteome-BSite: predicted binding sites and ligands in human 3D proteome
Authors: Sim Jiho , Kwon Sohee , Seok Chaok 
Published: October 2022

Abstract
Atomic-level knowledge of protein-ligand interactions allows a detailed understanding of protein functions and provides critical clues to discovering molecules regulating the functions. While recent innovative deep learning methods for protein structure prediction dramatically increased the structural coverage of the human proteome, molecular interactions remain largely unknown. A new database, HProteome-BSite, provides predictions of binding sites and ligands in the enlarged 3D human proteome. The model structures for human proteins from the AlphaFold Protein Structure Database were processed to structural domains of high confidence to maximize the coverage and reliability of interaction prediction. For ligand binding site prediction, an updated version of a template-based method GalaxySite was used. A high-level performance of the updated GalaxySite was confirmed. HProteome-BSite covers 80.74% of the UniProt entries in the AlphaFold human 3D proteome. Predicted binding sites and binding poses of potential ligands are provided for effective applications to further functional studies and drug discovery. The HProteome-BSite database is available at https://galaxy.seoklab.org/hproteome-bsite/database and is free and open to all users.