bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis
Authors: Guclu Tandac F. , Atilgan Ali Rana , Atilgan Canan 
Published: June 2024

ABSTRACTMutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we performin-silicomutational scanning for all possible single mutations, along with 2-µs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility (RSA) of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. Our findings pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.
Comparing statistical learning methods for complex trait prediction from gene expression
Authors: Arango Noah Klimkowski , Morgante Fabio 
Published: June 2024

AbstractAccurate prediction of complex traits is an important task in quantitative genetics that has become increasingly relevant for personalized medicine. Genotypes have traditionally been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regressions, dimension reductions, and machine learning methods. Recent studies have shown that gene expression levels can produce higher prediction accuracy than genotypes. However, only a few prediction methods were used in these studies. Thus, a comprehensive assessment of methods is needed to fully evaluate the potential of gene expression as a predictor of complex trait phenotypes. Here, we used data from theDrosophilaGenetic Reference Panel (DGRP) to compare the ability of several existing statistical learning methods to predict starvation resistance from gene expression in the two sexes separately. The methods considered differ in assumptions about the distribution of gene effect sizes – ranging from models that assume that every gene affects the trait to more sparse models – and their ability to capture gene-gene interactions. We also used functional annotation (i.e., Gene Ontology (GO)) as an external source of biological information to inform prediction models. The results show that differences in prediction accuracy between methods exist, although they are generally not large. Methods performing variable selection gave higher accuracy in females while methods assuming a more polygenic architecture performed better in males. Incorporating GO annotations further improved prediction accuracy for a few GO terms of biological significance. Biological significance extended to the genes underlying highly predictive GO terms with different genes emerging between sexes. Notably, the Insulin-like Receptor (InR) was prevalent across methods and sexes. Our results confirmed the potential of transcriptomic prediction and highlighted the importance of selecting appropriate methods and strategies in order to achieve accurate predictions.
Genetic Structuring and Conservation of Asian Sockeye Salmon: Identification of Regional Stock Complexes
Authors: Khrustaleva Anastasia M. 
Published: June 2024

AbstractIn order to describe large-scale spatial structure of Asian sockeye salmon the variability of 45 SNP loci was analyzed in 22 samples from the North-West coast of the Pacific Ocean. Three large regional population complexes were identified: southwestern Kamchatka, Kamchatka River basin, and the North-East (comprising stocks from Koryak Highlands). Populations within the identified complexes are connected by gene migration and have a common origin, close geographic proximity, comparable climatic, landscape and environmental conditions in the freshwater and early marine periods of life. Populations confined to watersheds of the North coast of the Sea of Okhotsk (Palana and Okhota rivers), along with island populations, displayed noteworthy distinctions from the isolated population complexes. We hypothesize that the marked divergence observed in island populations is primarily caused by genetic drift occurring during long periods of isolation. The pronounced divergence of Palana River population may be the result of both genetic drift and natural selection, driven by the challenging smoltification and juvenile transition to the ocean, along with local adaptations during spawning and early life periods in the Palansky Lake. At the same time in the Okhota River population, demographic factors such as genetic drift and bottlenecks played a key role.
Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction
Authors: Taguchi Y-h , Turki Turki 
Published: June 2024

AbstractThe evaluation of drug-gene-disease interactions is key for the identification of drugs effective against disease. However, at present, drugs that are effective against genes that are critical for disease are difficult to identify. Following a disease-centric approach, there is a need to identify genes critical to disease function and find drugs that are effective against them. By contrast, following a drug-centric approach comprises identifying the genes targeted by drugs, and then the diseases in which the identified genes are critical. Both of these processes are complex. Using a gene-centric approach, whereby we identify genes that are effective against the disease and can be targeted by drugs, is much easier. However, how such sets of genes can be identified without specifying either the target diseases or drugs is not known. In this study, a novel artificial intelligencebased approach that employs unsupervised methods and identifies genes without specifying neither diseases nor drugs is presented. To evaluate its feasibility, we applied tensor decomposition (TD)-based unsupervised feature extraction (FE) to perform drug repositioning from protein-protein interactions (PPI) without any other information. Proteins selected by TD-based unsupervised FE include many genes related to cancers, as well as drugs that target the selected proteins. Thus, we were able to identify cancer drugs using only PPI. Because the selected proteins had more interactions, we replaced the selected proteins with hub proteins and found that hub proteins themselves could be used for drug repositioning. In contrast to hub proteins, which can only identify cancer drugs, TD-based unsupervised FE enables the identification of drugs for other diseases. In addition, TD-based unsupervised FE can be used to identify drugs that are effective inin vivoexperiments, which is difficult when hub proteins are used. In conclusion, TD-based unsupervised FE is a useful tool for drug repositioning using only PPI without other information.
Spatial Multiomics Lipids and Gene expression using MALDI ISH MSI
Authors: Vanderschoot Kyle A. , Padilla Jacob P. , Steineman Kelli A. , De Caro Christopher M. , Heffern Marie C. , Neumann Elizabeth K. 
Published: June 2024

AbstractCurrent spatial gene expression methods use DNA microarrays, Next Generation Sequencing (NGS), and fluorescence microscopy to depict the pathological/histological architecture of tissues. While each of these techniques has its own advantages, they are often costly, time intensive, and limit sampling area. A newly developed mass spectrometry-based platform, MADLI ISH MSI, combinesin-situhybridization (ISH) with matrix-assisted laser desorption/ionization (MALDI) to indirectly detect mRNA through an azide-modified photocleavable peptide mass tag using a single RNA targeting probe sequence. To date, 20 photocleavable mRNA probes have been synthesized to provide cellular identity within full sagittal sections of fresh frozen murine brain. This information can then be combined with existing MALDI techniques to overlay metabolomic data, such as lipids, to connect the functional state of a cell with its expressed genes. Future directions include expanding upon the number of genes that can be targeted within a single experiment.
A systematic review on diagnostic and prognostic biomarkers for bladder cancer
Authors: Muhammad Umar , Ahmad Umar , Ibrahim Buhari , Ahmad Aliyu Adamu , Liman Haruna Usman 
Published: June 2024

AbstractBackgroundBladder cancer is one of the most prevalent malignancies worldwide. Despite its high incidence, public awareness of the condition remains low, and it has received less research attention compared to other common cancers. Over the past 80 years, patient outcomes and treatment strategies have remained largely unchanged, with cystoscopy being the primary method for detecting bladder cancer. This procedure, often repeated during long-term surveillance due to the recurrent nature of bladder tumors, is both uncomfortable for patients and costly for healthcare providers. The identification and validation of molecular biomarkers in blood, urine, or tissue could facilitate tumour detection and reduce reliance on cystoscopy.AimThis study aims to identify potential molecular biomarkers for bladder cancer that could improve tumour detection and lessen the need for repeated cystoscopies.MethodsA systematic review was conducted, searching for articles related to bladder cancer biomarkers in four databases: PubMed, ScienceDirect, Google Scholar, and Cochrane. Studies that met the inclusion criteria underwent title/abstract screening and full-text review. A total of twenty studies were deemed eligible for inclusion in this review.ResultsThe review identified several gene product biomarkers, including TEAD4, TPM1, TPM2, SKA3, EO1, HYAL3, MTDH, EPDR1, hTERT, KRT7, SW, ARHGAP9, XPH4, OTX1, BUB1, and Usp28. Additionally, protein product biomarkers were identified, such as A1AT, APOE, AG, CA9, IL8, MMP9, MMP10, PAI1, SCDI1, SDC1, VEGFA, CD73, TIP2, CXCL5, PCAT6, and NCR3LG1 (B7-H6).ConclusionThe study highlights the potential of various gene and protein biomarkers for the detection of bladder cancer. Further research is necessary to validate these biomarkers’ diagnostic and prognostic potential in identifying bladder cancer in suspected cases.
Mathematical and Statistical Approaches in Epidemiological Investigation of Hospital Infection: A Case Study of the 2015 Middle East Respiratory Syndrome Outbreak in Korea
Authors: Ko Youngsuk , Jung Eunok 
Published: June 2024

Summary IntroductionEpidemiological investigations are used to identify outbreaks, collect data, and implement control measures, playing a crucial role in disease control and prevention. Mathematical and statistical approaches enhance these investigations by incorporating data analysis to understand disease characteristics and provide insights.MethodsTo estimate the transmissibility of a disease, we introduce a process to derive the likelihood function using individual patient information from epidemiological investigation. This method was applied to the case of Pyeongtaek St. Mary’s Hospital during the 2015 Middle East Respiratory Syndrome outbreak in Korea. A stochastic model was developed, and scenario analysis reflecting actual outbreak progress, risk factors, and mask mandates was conducted.ResultsWe applied transmission rate estimation to the Pyeongtaek St. Mary’s Hospital case, showing a high patient-to-patient transmission rate. The superspreader was observed to have approximately 25 times higher transmissibility than other patients. Given these conditions, if hospital transmission period is prolonged, number of cases could be three times higher than the actual incidence. The effect of mask-wearing in hospital was investigated based on the type of mask and the intensity of the intervention. It was found that the scale of epidemic could be reduced by a maximum of 77% and a minimum of 17%.ConclusionsThrough the application of mathematical and statistical methodologies in epidemiological investigations, this study identified and quantified risk factors. Methodology of this study can be easily adapted and applied to other diseases and is expected to help in establishing effective strategies to fight against emerging infectious diseases.
Empirical evidence of a role for insertion sequences in the repair of DNA breaks in bacterial genomes
Authors: Ngan Wing Y. , Parab Lavisha , Bertels Frederic , Gallie Jenna 
Published: June 2024

AbstractInsertionSequences (ISs) are mobile pieces of DNA that are widespread in bacterial genomes. IS movements typically involve (i) excision of the IS element, (ii) cutting of the target site DNA, and (iii) IS element insertion. This process generates a new copy of the IS element, as well as a short duplication at the target site. It has been noted that, when observing extant IS element copies in a genome, occasionally noTargetSiteDuplication (TSD) is readily identifiable. This has been attributed to degeneration of the TSD at some point after the insertion event. Here, we provide evidence that some IS movement events – namely, those that occur in association with large-scale genome rearrangements – occur without generating TSDs. In support of this hypothesis, we provide two direct, empirical observations of such IS transposition events: an IS481movement occurring with a large duplication inPseudomonas fluorescensSBW25, and an IS5/IS1182movement plus a large deletion inEscherichia coliC. Additionally, we use sequencing data from the Lenski long-term evolution experiment to provide a further 14 examples of IS150movements inE. coliB that are associated with large deletions and do not carry TSDs. Overall, our results indicate that some IS elements can insert into, and thus repair, existing DNA breaks in bacterial genomes.
AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron
Authors: Yao Dengju , Zhang Xuehui , Zhan Xiaojuan 
Published: June 2024

AbstractIncreased evidence suggests that long non-coding RNA (lncRNA) holds a vital position in intricate human diseases. Nonetheless, the current pool of identified lncRNA linked to diseases remains restricted. Hence, the scientific community emphasizes the need for a reliable and cost-effective computational approach to predict the probable correlations between lncRNA and diseases. It would facilitate the exploration of the underlying mechanisms of lncRNA in ailments and the development of novel disease treatments. In this study, we propose a novel approach for predicting the associations between lncRNAs and diseases, which relies on the adaptive meta-path generation (AMPGLDA). Firstly, we integrate information about lncRNA, diseases, and miRNAs to construct a heterogeneous graph. Then, we utilize principal component analysis to extract global features from nodes. Based on this heterogeneous graph, AMPGLDA adaptively generates multiple meta-path graph structures and uses a graph convolutional neural network to learn the semantic feature representations of lncRNA and disease from the meta-path. Ultimately, AMPGLDA utilizes a deep neural network classifier to accurately predict the association between lncRNA and disease. The AMPGLDA model achieves impressive results, with AUC and AUPR scores of 99.66% and 99.66%, respectively, under the independent test set. Furthermore, three case studies demonstrate its accuracy in discovering new lncRNA-disease associations.
Potent and selective ‘genetic zipper’ method for plant protection: innovative DNA psyllidicides againstTrioza alacrisFlor based on short unmodified antisense oligonucleotides targeting rRNA of the pest
Authors: Oberemok V.V. , Novikov I.A. , Yatskova E.V. , Bilyk A.I. , Sharmagiy A.K. , Gal’chinsky N.V. 
Published: June 2024

AbstractChemical insecticides increased the chemical burden on natural ecosystems posing environmental health risk factor. The urgent need for a more sustainable and ecological approach has produced many innovative ideas, including eco-friendly ‘genetic zipper’ method (or CUAD platform) based on contact oligonucleotide insecticides. Oligonucleotide insecticides have enjoyed success recently on many sternorrhynchans showing highly adaptable structure for distinct insect pest species and selective mode of action. In this article, we describe the efficiency of the oligonucleotide insecticides (briefly, olinscides or DNA insecticides) Alacris-11 and Laura-11, as well as their combined use in mixture (1:1), designed for control of bay sucker (Trioza alacrisFlor), an important psyllid pest of noble laurel (Laurus nobilisL.). These olinscides are based on short unmodified antisense DNA oligonucleotides that target ITS2 between 5.8S rRNA and 28S rRNA in pre-rRNA (Laura-11) and 28S rRNA region in mature 28S rRNA and pre-rRNA (Alacris-11). The maximum pest mortality, observed on 14thday of the experiment, comprised 95.01 ± 4.42 % for Alacris-11, 97.16 ± 2.48 % for Laura-11, and 98.72 ± 1.14 % for their mixture (1:1). The control oligonucleotide CTGA-11 did not cause any significant mortality (9.38 ± 0.57 %), emphasizing selectivity in the action of oligonucleotide insecticides. The results show potent and specific nature of oligonucleotide insecticides for pest control and opens up new frontiers in control of economically important psyllids in agriculture and forestry, including Asian citrus psyllid (Diaphorina citriKuwayama) and many others. Scientists can easily adopt ‘genetic zipper’ method for plethora of insect pests because DNA is a programmable molecule and provides game-changing characteristics for plant projection.
Different Trajectories of Functional Connectivity Captured with Gamma-Event Coupling and Broadband Measures of EEG in the Rat Fluid Percussion Injury Model
Authors: Fox Rachel , Santana-Gomez Cesar , Shamas Mohamad , Pavade Aarja , Staba Richard , Harris Neil G. 
Published: June 2024

AbstractFunctional connectivity (FC) after TBI is affected by an altered excitatory-inhibitory balance due to neuronal dysfunction, and the mechanistic changes observed could be reflected differently by contrasting methods. Local gamma event coupling FC (GEC-FC) is believed to represent multiunit fluctuations due to inhibitory dysfunction, and we hypothesized that FC derived from widespread, broadband amplitude signal (BBA-FC) would be different, reflecting broader mechanisms of functional disconnection. We tested this during sleep and active periods defined by high delta and theta EEG activity, respectively, at 1,7 and 28d after rat fluid-percussion-injury (FPI) or sham injury (n=6/group) using 10 indwelling, bilateral cortical and hippocampal electrodes. We also measured seizure and high-frequency oscillatory activity (HFOs) as markers of electrophysiological burden. BBA-FC analysis showed early hyperconnectivity constrained to ipsilateral sensory-cortex-to-CA1-hippocampus that transformed to mainly ipsilateral FC deficits by 28d compared to shams. These changes were conserved over active epochs, except at 28d when there were no differences to shams. In comparison, GEC-FC analysis showed large regions of hyperconnectivity early after injury within similar ipsilateral and intrahemispheric networks. GEC-FC weakened with time, but hyperconnectivity persisted at 28d compared to sham. Edge- and global connectivity measures revealed injury-related differences across time in GEC-FC as compared to BBA-FC, demonstrating greater sensitivity to FC changes post-injury. There was no significant association between sleep fragmentation, HFOs, or seizures with FC changes. The within-animal, spatial-temporal differences in BBA-FC and GEC-FC after injury may represent different mechanisms driving FC changes as a result of primary disconnection and interneuron loss.Significance statementThe present study adds to the understanding of functional connectivity changes in preclinical models of traumatic brain injury. In previously reported literature, there is heterogeneity in the directionality of connectivity changes after injury, resulting from factors such as severity of injury, frequency band studied, and methodology used to calculate FC. This study aims to further clarify differential mechanisms that result in altered network topography after injury, by using Broadband Amplitude-Derived FC and Gamma Event Coupling-Derived FC in EEG. We found post-injury changes that differ in complexity and directionality between measures at and across timepoints. In conjunction with known results and future studies identifying different neural drivers underlying these changes, measures derived from this study could provide useful means from which to minimally-invasively study temporally-evolving pathology after TBI.
Ephrin Forward Signaling Controls Interspecies Cell Competition in Pluripotent Stem Cells
Authors: Tanaka Junichi , Kondo Yuri , Sakurai Masahiro , Sawada Anri , Hwang Youngmin , Miura Akihiro , Shimamura Yuko , Shimizu Dai , Hu Yingying , Sarmah Hemanta , Ninish Zurab , Cai James , Wu Jun , Mori Munemasa 
Published: June 2024

SummaryIn the animal kingdom, evolutionarily conserved mechanisms known as cell competition eliminate unfit cells during development. Interestingly, cell competition also leads to apoptosis of donor cells upon direct contact with host cells from a different species during interspecies chimera formation. The mechanisms underlying how host animal cells recognize and transmit cell death signals to adjacent xenogeneic human cells remain incompletely understood. In this study, we developed an interspecies cell contact reporter system to dissect the mechanisms underlying competitive interactions between mouse and human pluripotent stem cells (PSCs). Through single-cell RNA-seq analyses, we discovered that Ephrin A ligands in mouse cells play a crucial role in signaling cell death to adjacent human cells that express EPHA receptors during interspecies PSC co-culture. We also demonstrated that blocking the Ephrin A-EPHA receptor interaction pharmacologically, and inhibiting Ephrin forward signaling genetically in the mouse cells, enhances the survival of human PSCs and promotes chimera formation bothin vitroandin vivo. Our findings elucidate key mechanisms of interspecies PSC competition during early embryogenesis and open new avenues for generating humanized tissues or organs in animals, potentially revolutionizing regenerative medicine.