bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive Interactome Mapping of the DNA Repair Scaffold SLX4 using Proximity Labeling and Affinity Purification
Authors: Aprosoff Camila M. , Dyakov Boris J.A. , Cheung Vivian H.W. , Wong Cassandra J. , Palandra Mikaela , Gingras Anne-Claude , Wyatt Haley D.M. 
Published: September 2022

ABSTRACTThe DNA repair scaffold SLX4 has pivotal roles in cellular processes that maintain genome stability, most notably homologous recombination. Germline mutations in SLX4 are associated with Fanconi anemia, a disease characterized by chromosome instability and cancer susceptibility. The role of mammalian SLX4 in homologous recombination depends critically on binding and activating structure-selective endonucleases, namely SLX1, MUS81-EME1, and XPF-ERCC1. Increasing evidence indicates that cells rely on distinct SLX4-dependent complexes to remove DNA lesions in specific regions of the genome. Despite our understanding of SLX4 as a scaffold for DNA repair proteins, a detailed repertoire of SLX4 interactors has never been reported. Here, we provide the first comprehensive map of the human SLX4 interactome using proximity-dependent biotin identification (BioID) and affinity purification coupled to mass spectrometry (AP-MS). We identified 237 high-confidence interactors, of which the vast majority represent novel SLX4 binding proteins. Network analysis of these hits revealed pathways with known involvement of SLX4, such as DNA repair, and novel or emerging pathways of interest, including RNA metabolism and chromatin remodeling. In summary, the comprehensive SLX4 interactome we report here provides a deeper understanding of how SLX4 functions in DNA repair while revealing new cellular processes that may involve SLX4.
Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials
Authors: Gong Tiansu , Ju Fusong , Bu Dongbo 
Published: September 2022

AbstractPseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of Knot-Fold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using a self-attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially-designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely-used dynamic programming algorithms, thus facilitating the identification of pseudoknots. Using a total of 1605 RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy significantly higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities.
Kidney-specific methylation patterns correlate with kidney function and are lost upon kidney disease progression
Authors: Sagy Naor , Meyrom Noa , Beckerman Pazit , Pleniceanu Oren , Bar Daniel Z 
Published: September 2022

AbstractChronological and biological age correlate with DNA methylation levels at specific sites in the genome. Linear combinations of multiple methylation sites, termed epigenetic clocks, can inform us of the chronological age and predict multiple health-related outcomes. However, why some sites correlate with lifespan, healthspan, or specific medical conditions remains poorly understood. Kidney fibrosis is the common pathway for Chronic Kidney Disease, which affects 10% of Europe and USA population. Here we identify epigenetic clocks and methylation sites that correlate with kidney function. Moreover, we identify methylation sites that have a unique methylation signature in the kidney. Methylation levels in the majority of these sites correlates with kidney state and function. When kidney function deteriorates, all of these sites regress towards the common methylation pattern observed in other tissues. Interestingly, while the majority of sites are less methylated in the kidney and become more methylated with loss of function, a fraction of the sites are highly methylated in the kidney and become less methylated when kidney function declines. These methylation sites are enriched for specific transcription-factor binding sites. In a large subset of sites, changes in methylation pattern are accompanied by changes in gene expression in kidneys of chronic kidney disease patients. These results support the information theory of aging, and the hypothesis that the unique tissue identity, as captured by methylation patterns, is lost as tissue function declines. However, this information loss is not random, but guided towards a baseline that is dependent on the genomic loci.
A benchmarking of human Y-chromosomal haplogroup classifiers from whole-genome and whole-exome sequence data
Authors: García-Olivares Víctor , Muñoz-Barrera Adrián , Rubio-Rodríguez Luis A. , Jáspez David , Díaz-de Usera Ana , Iñigo Campos Antonio , Veeramah Krishna R. , Alonso Santos , Thomas Mark G. , Lorenzo-Salazar José M. , González-Montelongo Rafaela , Flores Carlos 
Published: September 2022

AbstractThe non-recombinant region of the Y chromosome (NRY) contains a great number of polymorphic markers that allows to accurately reconstruct pedigree relationships and retrieve ancestral information from study samples. The analysis of NRY is typically implemented in anthropological, medical, and forensic studies. High-throughput sequencing (HTS) has profoundly increased the identification of genetic markers in the NRY genealogy and has prompted the development of automated NRY haplogroup classification tools. Here, we present a benchmarking study of five command-line tools for NRY haplogroup classification. The evaluation was done using empirical short-read HTS data from 50 unrelated donors using paired data from whole-genome sequencing (WGS) and whole-exome sequencing (WES) experiments. Besides, we evaluate the performance of the top-ranked tool in the classification of data of third generation HTS obtained from a subset of donors. Our findings demonstrate that WES can be an efficient approach to infer the NRY haplogroup, albeit generally providing a lower level of genealogical resolution than that recovered by WGS. Among the tools evaluated, YLeaf offers the best performance for both WGS and WES applications. Finally, we demonstrate that YLeaf is able to correctly classify all samples sequenced with nanopore technology from long noisy reads.
Can neural correlates of encoding explain the context dependence of reward-enhanced memory?
Authors: Hellerstedt Robin , Bekinschtein Tristan , Talmi Deborah 
Published: September 2022

AbstractSelective encoding can be studied by manipulating how valuable it is for participants to remember specific stimuli, for instance by varying the monetary reward participants receive for recalling a particular stimulus in a subsequent memory test. It would be reasonable for participants to strategically attend more to high-reward items compared to low-reward items in mixed list contexts, but to attend both types of items equally in pure list contexts, where all items are of equal value. Reward-enhanced memory may be driven by automatic dopaminergic interactions between reward circuitry and the hippocampus and thus be insensitive to list context; or it may be driven by meta-cognitive strategies, and thus context-dependent. We contrasted these alternatives by manipulating list composition, and tracked selective encoding through multiple EEG measures of attention and rehearsal. Behavioural results were context-dependent, such that recall of high-reward items was increased only in mixed lists. This result and aspects of the recall dynamics confirm predictions of the eCMR (emotional Context Maintenance and Retrieval) model. The power of ssVEPs was lower for high-reward items regardless of list composition, suggesting decreased visual processing of high-reward stimuli and that ssVEPs may index the modulation of context-to-item associations predicted by eCMR. By contrast, reward modulated the amplitude of Late Positive Potential and Frontal Slow Wave only in mixed lists. Taken together the results provide evidence that reward-enhanced memory is caused by an interplay between strategic processes applied when high- and low-reward items compete for cognitive resources during encoding and context-dependent mechanisms operating during recall.
Human immunodeficiency virus integration complexes are active following ordered addition of wild type integrase, viral DNA, and LEDGF/p75
Authors: Rabe Anthony J. , Russo Jacob A. , Larue Ross C. , Yoder Kristine E. 
Published: September 2022

AbstractHuman immunodeficiency virus (HIV-1) requires integration of the viral genome into the host DNA for replication. Efficient HIV-1 integration employs a host co-factor LEDGF/p75 to stabilize the HIV-1 integration complex and tether that complex to host chromatin. Integration may be studied with purified components HIV-1 integrase (IN), LEDGF/p75, and DNA mimicking the ends of the viral DNA genome (vDNA) assembled as an intasome. There is a likely order of addition during infection with HIV-1 IN binding to vDNA before encountering LEDGF/p75. However, the ordered assembly of wild type HIV-1 IN, LEDGF/p75, and oligomer vDNA has not been tested. Variable assemblies occurred on ice before the addition of target DNA. Incubation on ice and addition of LEDGF/p75 were required to assemble complexes capable of efficient concerted integration. Integration efficiency following variable order of addition of intasome components was greatest when LEDGF/p75 was added last to preassembled HIV-1 IN and vDNA.
Nuclear morphology predicts cell survival to cisplatin chemotherapy
Authors: Kim Chi-Ju , Gonye Anna LK , Truskowski Kevin , Lee Cheng-Fan , Cho Yoon-Kyoung , Austin Robert H , Pienta Kenneth J , Amend Sarah R 
Published: September 2022

AbstractIn this study, we characterized nuclear morphology and function as cancer cells underwent recovery following chemotherapeutic treatment to identify the unique characteristics associated with treatment resistance and successful survival. Cells that survived following treatment and resisted therapy-induced cell death were predominantly mononucleated with increased nuclear/cellular size, enabled by continuous endocycling. We found that cells that survive after therapy release likely employ more efficient DNA damage repair and exhibit a distinct nucleolar phenotype - fewer but larger nucleoli – and increased rRNA levels. These data support a paradigm where soon after therapy release, the treated population mostly contains cells with a high level of widespread and catastrophic DNA damage that leads to apoptosis, while the minority of cells that have successful DDR are more likely to access a pro-survival state. These findings suggest that one way cancer cells can survive systemic therapy is to enter the polyaneuploid cancer cell (PACC) state, a recently-described mechanism of therapy resistance. Cancer cells in this state are physically enlarged, undergo whole-genome doubling resulting in polyaneuploid genomes, and are associated with worse prognosis in cancer patients. The PACC state is accessed when a cancer cell experiences external stress, such as genotoxic chemotherapy; after a period of recovery, cells exit the PACC state and resume proliferation to repopulate the tumor cell pool. Our findings demonstrate the fate of cancer cells following chemotherapy treatment and define key characteristics of the resistant PACC state. This work is essential for understanding and, ultimately, targeting, cancer resistance and recurrence.
Inducible CRISPR epigenome systems mimic cocaine induced bidirectional regulation of Nab2 and Egr3
Authors: Choi Eric Y. , Franco Daniela , Stapf Catherine A. , Gordin Madeleine , Chow Amanda , Cover Kara K. , Chandra Ramesh , Lobo Mary Kay 
Published: September 2022

AbstractSubstance use disorder is a debilitating chronic disease and a leading cause of disability around the world. The nucleus accumbens (NAc) is a major brain hub that mediates reward behavior. Studies demonstrate exposure to cocaine is associated with molecular and functional imbalance in two NAc medium spiny neuron subtypes (MSNs), dopamine receptor 1 and 2 enriched D1-MSNs and D2-MSNs. Our previous reports showed that repeated cocaine exposure induced transcription factor early growth response 3 (Egr3) mRNA in NAc D1-MSNs, while reducing it in D2-MSNs. Here, we report our findings of repeated cocaine exposure inducing cell subtype specific bidirectional expression of the Egr3 corepressor NGFI-A-binding protein 2 (Nab2). Using CRISPR activation and interference (CRISPRa and CRISPRi) tools combined with Nab2 or Egr3 targeted sgRNAs, we mimicked these bidirectional changes in Neuro2a cells. Furthermore, we investigated D1-MSN and D2-MSN subtype specific expressional changes of histone lysine demethylases Kdm1a, Kdm6a and Kdm5c in NAc after repeated cocaine exposure. Since Kdm1a showed bidirectional expression patterns in D1-MSNs and D2-MSNs, like Egr3, we developed a light inducible Opto-CRISPR-KDM1a system. We were able to downregulate Egr3 and Nab2 transcripts and cause bidirectional expression changes in D1-MSNs and D2-MSNs similar to cocaine exposure in Neuro2A cells. In contrast, our Opto-CRISPR-p300 activation system induced the Egr3 and Nab2 transcripts and caused bidirectional transcription regulations in D1-MSNs and D2-MSNs. Our study sheds light on the expression patterns of Nab2 and Egr3 in specific NAc MSN subtypes in cocaine action and uses CRISPR tools to further mimic these expression patterns.
Interpretable machine learning with tree-based shapley additive explanations: application to metabolomics datasets for binary classification
Authors: Bifarin Olatomiwa O. 
Published: September 2022

AbstractMachine learning (ML) models are used in clinical metabolomics studies most notably for biomarker discoveries, to identify metabolites that discriminate between a case and control group. To improve understanding of the underlying biomedical problem and to bolster confidence in these discoveries, model interpretability is germane. In metabolomics, partial least square discriminant analysis (PLS-DA) and its variants are widely used, partly due to the model’s interpretability with the Variable Influence in Projection (VIP) scores, a global interpretable method. Herein, Tree-based Shapley Additive explanations (SHAP), an interpretable ML method grounded in game theory, was used to explain ML models with local explanation properties. In this study, ML experiments (binary classification) were conducted for three published metabolomics datasets using PLS-DA, random forests, gradient boosting, and extreme gradient boosting (XGBoost). Using one of the datasets, PLS-DA model was explained using VIP scores, while a tree-based model was interpreted using Tree SHAP. The results show that SHAP has a more explanation depth than PLS-DA’s VIP, making it a powerful method for rationalizing machine learning predictions from metabolomics studies.
DNA processing by the Kaposi’s sarcoma-associated herpesvirus alkaline exonuclease SOX contributes to viral gene expression and infectious virion production
Authors: Hartenian Ella , Mendez Aaron S. , Didychuk Allison L. , Khosla Shivani , Glaunsinger Britt A. 
Published: September 2022

AbstractAlkaline exonucleases (AE) are present in several large DNA viruses including bacteriophage λ and herpesviruses, where they play roles in viral DNA processing during genome replication. Given the genetic conservation of AEs across viruses infecting different kingdoms of life, these enzymes likely assume central roles in the lifecycles of viruses where they have yet to be well characterized. Here, we applied a structure-guided functional analysis of the bifunctional AE in the oncogenic human gammaherpesvirus Kaposi’s sarcoma-associated herpesvirus (KSHV), called SOX. In addition to identifying a preferred DNA substrate preference for SOX, we define key residues important for DNA binding and DNA processing, and how SOX activity on DNA partially overlaps with its functionally separable cleavage of mRNA. By engineering these SOX mutants into KSHV, we reveal roles for its DNase activity in viral gene expression and infectious virion production. Our results provide mechanistic insight into gammaherpesviral AE activity as well as areas of functional conservation between this mammalian virus AE and its distant relative in phage λ.
Minimal cell JCVI-syn3B as a chassis to reveal the mechanisms behind Mycoplasma host–pathogen interactions
Authors: de C. Bittencourt Daniela M. , Brown David M. , Assad-Garcia Nacyra , Lynott Michaela R. , Sun Lijie , Palhares de Melo Luis Alberto M. , Freire Marcelo , Glass John I. 
Published: September 2022

AbstractMycoplasmas are atypical bacteria that are obligate parasites of animals and plants. They are known for their capacity to contaminate and parasitize mammalian cell cultures, thereby offering fortuitous models to examine the host-microbe interaction. We used a near wildtype strain of the goat pathogen Mycoplasma mycoides (Mmc) and several minimized Mmc strains lacking genes not essential for growth in laboratory media to investigate host-mycoplasma interactions. Stains with near minimal genomes were incapable of surviving in co-culture with mammalian HEK-293T and HeLa cells. We identified a cluster of eight non-essential genes that when added back to the minimized strains enabled mycoplasma attachment to mammalian cells. Those genes did not restore the capacity of the minimal cell to grow when co-cultured with mammalian cells indicating processes of attaching to mammalian cells and parasitism involve different genes. Furthermore, minimized Mmc strains were not phagocytized by human myeloid cells unlike the near wildtype Mmc.
Discovery of topic evolution path and semantic relationship based on patent entity representation
Authors: Zhang Jinzhu , Liu Yue , Jiang Linqi , Shi Jialu 
Published: September 2022

PurposeThis paper aims to propose a method for better discovering topic evolution path and semantic relationship from the perspective of patent entity extraction and semantic representation. On the one hand, this paper identifies entities that have the same semantics but different expressions for accurate topic evolution path discovery. On the other hand, this paper reveals semantic relationships of topic evolution for better understanding what leads to topic evolution.Design/methodology/approachFirstly, a Bi-LSTM-CRF (bidirectional long short-term memory with conditional random field) model is designed for patent entity extraction and a representation learning method is constructed for patent entity representation. Secondly, a method based on knowledge outflow and inflow is proposed for discovering topic evolution path, by identifying and computing semantic common entities among topics. Finally, multiple semantic relationships among patent entities are pre-designed according to a specific domain, and then the semantic relationship among topics is identified through the proportion of different types of semantic relationships belonging to each topic.FindingsIn the field of UAV (unmanned aerial vehicle), this method identifies semantic common entities which have the same semantics but different expressions. In addition, this method better discovers topic evolution paths by comparison with a traditional method. Finally, this method identifies different semantic relationships among topics, which gives a detailed description for understanding and interpretation of topic evolution. These results prove that the proposed method is effective and useful. Simultaneously, this method is a preliminary study and still needs to be further investigated on other datasets using multiple emerging deep learning methods.Originality/valueThis work provides a new perspective for topic evolution analysis by considering semantic representation of patent entities. The authors design a method for discovering topic evolution paths by considering knowledge flow computed by semantic common entities, which can be easily extended to other patent mining-related tasks. This work is the first attempt to reveal semantic relationships among topics for a precise and detailed description of topic evolution.
Ex-auditor executives and investment efficiency: evidence from Indonesia
Authors: Ngelo Agnes Aurora , Harymawan Iman , Nasih Mohammad 
Published: September 2022

PurposeThis study aims to examine the relationship between the presence of ex-auditor chief executive officers (CEOs) and ex-auditor chief financial officers (CFOs) with the company's investment efficiency decisions.Design/methodology/approachThe authors use non-financial Indonesian listed firms, and the authors obtain 2,763 firm-year observations of ex-auditor CEOs and 2,708 firm-year observations of ex-auditor CFOs from 2010–2019.FindingsThe results show that ex-auditor CEOs tend to make efficient investment decisions, while ex-auditor CFOs do not. However, when a company has a CEO and a CFO who are both former auditors, there is a significantly stronger positive relationship with investment efficiency. These results indicate that working experience as an auditor can optimally facilitate the decision regarding investment level. Moreover, the results suggest that the CEO, as top management, has more influence in providing the company's final investment decisions, whereas the CFO plays a role in providing investment recommendations to the CEO. The results of this study are consistent with the use of alternative measurements and the robustness test of Coarsened Exact Matching (CEM).Practical implicationsThe results of this study can contribute as material for consideration by company management in selecting company organs with an auditor background to secure efficient investment.Originality/valueThis study specifically examines the experience, values, and particular characteristics of top management with an auditor background on the company's strategic decisions. This study is also based on the phenomenon that the number of ex-auditor CEOs and CFOs in Indonesia tends to increase every year.