bluuebunny/crossref_metadata_2025_split huggingface dataset:
A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer
Authors: Zeng Jianhao , Singh Shambhavi , Jiang Ying , Casarez Eli , Atkins Kristen A. , Janes Kevin A. , Zong Hui 
Published: April 2023

AbstractBasal-like breast cancer is an aggressive breast cancer subtype, often characterized by a deficiency inBRCA1function and concomitant loss ofp53. While conventional mouse models enable the investigation of its malignant stages, one that reveals its initiation and pre-malignant progression is lacking. Here, we leveraged a mouse genetic system known asMosaicAnalysis withDoubleMarkers (MADM) to generate rare GFP-labeledBrca1,p53-deficient cells alongside RFP+ wildtype sibling cells in the mammary gland. The mosaicism resembles the sporadic initiation of human cancer and enables spatially resolved analysis of mutant cells in comparison to paired wildtype sibling cells. Mammary tumors arising in the model show transcriptomic and genomic characteristics similar to human basal-like breast cancer. Analysis of GFP+ mutant cells at interval time points before malignancy revealed a stepwise progression of lesions from focal expansion to hyper-alveolarization and then to micro-invasion. These stereotyped morphologies indicate the pre-malignant stage irrespective of the time point at which it is observed. Paired analysis of GFP-RFP siblings during focal expansion suggested that hyper-alveolarized structures originate from ductal rather than alveolar cells, despite their morphological similarities to alveoli. Evidence for luminal-to-basal transition at the pre-malignant stages was restricted to cells that had escaped hyper-alveoli and progressed to micro-invasive lesions. Our MADM-based mouse model presents a useful tool for studying the pre-malignancy of basal-like breast cancer.Summary statementA mouse model recapitulates the process of human basal-like breast tumorigenesis initiated from sporadicBrca1, p53-deficient cells, empowering spatially-resolved analysis of mutant cells during pre-malignant progression.
Motor unit tracking using blind source separation filters and waveform cross-correlations: reliability under physiological and pharmacological conditions
Authors: Goodlich Benjamin I. , Vecchio Alessandro Del , Kavanagh Justin J. 
Published: April 2023

ABSTRACTRecent advancements in the analysis of high-density surface electromyography (HDsEMG) have enabled the identification, and tracking, of motor units (MUs) to study muscle activation. This study aimed to evaluate the reliability of MU tracking using two common methods: blind source separation filters and two-dimensional waveform cross-correlation. An experiment design was developed to assess physiological reliability, and reliability for a drug intervention known to reduce the firing rate of motoneurones (cyproheptadine). HDsEMG signals were recorded from tibialis anterior during isometric dorsiflexions to 10%, 30%, 50% and 70% of maximal voluntary contraction. MUs were matched within session (2 hr) using the filter method, and between sessions (7 days) via the waveform method. Both tracking methods demonstrated similar reliability during physiological conditions (e.g., MU discharge: filter ICC 10% of MVC = 0.76, to 70% of MVC = 0.86; waveform ICC: 10% of MVC = 0.78, to 70% of MVC = 0.91). Although reliability slightly reduced after the pharmacological intervention, there were no discernible differences in tracking performance (e.g., MU disc filter ICC: 10% of MVC = 0.73, to 70% of MVC = 0.75; DR waveform ICC: 10% of MVC = 0.84, to 70% of MVC = 0.85). The poorest reliability typically occurred at higher contraction intensities, which aligned with the greatest variability in MU characteristics. This study confirms that tracking method may not impact the interpretation of MU data, provided that an appropriate experiment design is employed. However, caution should be used when tracking MUs during higher intensity isometric contractions.NEW AND NOTEWORTHYThe most direct way to validate longitudinal tracking of motor unit data extracted from high-density surface electromyography is to contrast findings with intramuscular electromyography. We use pharmacology to changes motor unit discharge properties as a non-invasive alternative to validate the reliability tracking motor units. This study confirmed that the specific tracking method may not impact interpretation of motor unit data at lower contraction intensities, however caution should be used when tracking units during higher intensities.
Fatal Iatrogenic Cerebral Amyloid-Related Encephalitis in a patient treated with lecanemab for Alzheimer’s disease: neuroimaging and neuropathology
Authors: Solopova Elena , Romero-Fernandez Wilber , Harmsen Hannah , Ventura-Antunes Lissa , Wang Emmeline , Shostak Alena , Maldonado Jose , Donahue Manus , Schultz Daniel , Coyne Thomas M. , Charidimou Andreas , Schrag Matthew 
Published: April 2023

AbstractWe report the case of an elderly woman in good general health aside from early-stage Alzheimer’s disease who was enrolled in a randomized controlled trial of the novel therapeutic monoclonal antibody lecanemab where she was treated with the placebo, and subsequently in the open label extension study where she received lecanemab infusions every two weeks. After the third infusion, she suffered a seizure followed by aphasia and progressively worsening encephalopathy. Magnetic resonance imaging revealed multifocal cerebral edema and an increased burden of cerebral microhemorrhages compared to pre-trial imaging, consistent with Amyloid Related Imaging Abnormality (ARIA). She was treated with an antiepileptic regimen and high-dose intravenous corticosteroids but continued to worsen and expired after five days in the hospital. The family requested an autopsy and consented to evaluation of her brain for research. Post-mortem MRI confirmed extensive microhemorrhagic changes in the temporal, parietal and occipital lobes, some of which were visible on gross inspection of the brain. Autopsy confirmed APOE genotype of E4/E4 and the presence of typical neuropathological features of Alzheimer’s disease along with severe cerebral amyloid angiopathy with inflammatory features, including perivascular lymphocytic infiltrates, reactive macrophages and fibrinoid degeneration of vessel walls. There were deposits of β-amyloid in meningeal vessels and penetrating arterioles with numerous microaneurysms. Cerebral microhemorrhages were associated with arterioles harboring β-amyloid deposits and having degenerative morphologies. We conclude from these results that the patient likely died as a result of severe cerebral amyloid angiopathy with marked microvascular degeneration and meningoencephalitis. Further study of the mechanism of ARIA and the neuropathological changes associated with plaque clearance are needed.
Improved gene annotation of the fungal wheat pathogenZymoseptoria triticibased on combined Iso-Seq and RNA-Seq evidence
Authors: Lapalu Nicolas , Lamothe Lucie , Petit Yohann , Genissel Anne , Delude Camille , Feurtey Alice , Abraham Leen N. , Smith Dan , King Robert , Renwick Alison , Appertet Mélanie , Sucher Justine , Steindorff Andrei S. , Goodwin Stephen B. , Kema Gert H.J. , Grigoriev Igor V. , Hane James , Rudd Jason , Stukenbrock Eva , Croll Daniel , Scalliet Gabriel , Lebrun Marc-Henri 
Published: April 2023

AbstractDespite large omics datasets, the establishment of a reliable gene annotation is still challenging for eukaryotic genomes. Here, we used the reference genome of the major fungal wheat pathogenZymoseptoria tritici(isolate IPO323) as a case study to develop methods to improve eukaryotic gene prediction. Four previous IPO323 annotations identified 10,933 to 13,260 gene models, but only one third of these coding sequences (CDS) have identical structures. To resolve these discrepancies and improve gene models, we generated full-length transcripts using long-read sequencing. This dataset was used together with other evidence (RNA-Seq transcripts and protein sequences) to generate novelab initiogene models. The selection of the best structure among novel and existing gene models was performed according to transcript and protein evidence using InGenAnnot, a novel bioinformatics suite. Overall, 13,414 re-annotated gene models (RGMs) were predicted, including 671 new genes among which 53 encoded effector candidates. This process corrected many of the errors (15%) observed in previous gene models (coding sequence fusions, false introns, missing exons). While fungal genomes have poor annotations of untranslated regions (UTRs), our Iso-Seq long-read sequences outlined 5’ and 3’UTRs for 73% of the RGMs. Alternative transcripts were identified for 13% of RGMs, mostly due to intron retention (75%), likely corresponding to unprocessed pre-mRNAs. A total of 353 genes displayed alternative transcripts with combinations of previously predicted or novel exons. Long non-coding transcripts (lncRNAs) and double-stranded RNAs from two fungal viruses were also identified. Most lncRNAs corresponded to antisense transcripts of genes (52%). lncRNAs that were up or down regulated during infection were enriched in antisense transcripts (70%), suggesting their involvement in the control of gene expression. Our results showed that combining differentab initiogene predictions and evidence-driven curation using InGenAnnot improved the quality of gene annotations of a compact eukaryotic genome. Our analysis also provided new insights into the transcriptional landscape ofZ. tritici, helping develop an increasingly complex picture of its biology.
Easy Removal of Steric Clashes and Entanglements in Macromolecular Systems by Temporary Addition of a Fourth Spatial Dimension
Authors: Elcock Adrian H. 
Published: April 2023

AbstractWhen models of complicated macromolecular systems are constructed, it is common to inadvertently include either gross steric clashes or entanglements of extended loop regions. Removing these problems with conventional energy minimization or dynamics algorithms can often be difficult. Here I show that one easy alternative is to temporarily add an extra spatial dimension and to displace atoms or molecules along this fourth dimension such that the distances between atoms, when measured in 4D, are no longer considered clashing. Adding in half-harmonic potential functions to mimic walls in this 4thdimension, and then moving these walls toward each other, has the effect of decreasing the space available in the 4thdimension and drives atoms to avoid each other in 3D. I illustrate the method with three examples: two showing how interlocked ring polymers can be easily disentangled from each other in both 2D and 3D, and one showing how ten identical coarse-grained protein models, all placed at the same point in 3D space, can be separated from each other, without distorting their structures, during the course of a single energy minimization. A sample program implementing the method is available that can be easily adapted to other situations.
Lack of mTORC2 signaling in CD11c+myeloid cells inhibits their migration and ameliorates experimental colitis
Authors: Ignacio Aline , Cipelli Marcella , Takiishi Tatiane , Aguiar Cristhiane Favero , Terra Fernanda Fernandes , Ghirotto Bruno , Silva Eloisa Martins , Castoldi Angela , Magalhães Yuli Thamires , Antonio Tiago , Hiyane Meire Ioshie , Andrade-Oliveira Vinicius , Forti Fabio Luis , Saraiva Camara Niels Olsen 
Published: April 2023

AbstractMammalian target of rapamycin (mTOR) pathway plays a key role in determining immune cells function through modulation of their metabolic status. By specific deletion of Rictor in tissue-resident CD11c+myeloid cells (CD11cRicΔ/Δ), this study investigated the role of mTOR complex 2 (mTORC2) signaling in dendritic cells (DCs) function in mice. We showed that upon DSS-induced colitis, lack of mTORC2 signaling CD11c+cells diminish colonic inflammation, abrogates dendritic cell (DC) migration to the mesenteric lymph nodes (MLN), thereby diminishing the infiltration of T helper (Th) 17 cells in the lamina propria (LP). These findings corroborate with abrogation of cytoskeleton organization and decreased activation of Rac1 and Cdc42 GTPases observed in CD11c+-mTORC2-deficient cells. Meta-analysis on colonic samples from ulcerative colitis (UC) patients revealed increased gene expression of pro-inflammatory cytokines which coincided with augmented expression of mTOR pathway, positive correlation between the DC marker ITGAX, and IL-6, the expression of RICTOR, and CDC42. Together, this work proposes that targeting mTORC2 on DCs offers a key to hamper inflammatory responses and this way, ameliorates the progression and severity of intestinal inflammatory diseases.
Deep Learning for Protein Structure Prediction: Advancements in Structural Bioinformatics
Authors: Szelogowski Daniel 
Published: April 2023

AbstractMotivationAccurate prediction of protein structures is crucial for understanding protein function, stability, and interactions, with far-reaching implications in drug discovery and protein engineering. As the fields of structural bioinformatics and artificial intelligence continue to converge, a standardized model for protein structure prediction is still yet to be seen as even large models like AlphaFold continue to change architectures. To this end, we provide a comprehensive literature review highlighting the latest advancements and challenges in deep learning-based structure prediction, as well as a benchmark system for structure prediction and visualization of amino acid protein sequences.ResultsWe present ProteiNN, a Transformer-based model for end-to-end single-sequence protein structure prediction, motivated by the need for accurate and efficient methods to decipher protein structures and their roles in biological processes and a system to perform prediction on user-input protein sequences. The model leverages the transformer architecture’s powerful representation learning capabilities to predict protein secondary and tertiary structures directly from integer-encoded amino acid sequences. Our results demonstrate that ProteiNN is effective in predicting secondary structures, though further improvements are necessary to enhance the model’s performance in predicting higher-level structures. This work thus showcases the potential of transformer-based architectures in structure prediction and lays the foundation for future research in structural bioinformatics and related fields.Availability and implementationThe source code of ProteiNN is available athttps://github.com/danielathome19/ProteiNN-Structure-Predictor.
Benchmarking Bioinformatic Virus Identification Tools Using Real-World Metagenomic Data across Biomes
Authors: Wu Ling-Yi , Pappas Nikolaos , Wijesekara Yasas , Piedade Gonçalo J. , Brussaard Corina P.D. , Dutilh Bas E. 
Published: April 2023

ABSTRACTAs most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training/reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance. We compared the performance of ten state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools had highly variable true positive rates (0 – 68%) and false positive rates (0 – 15%). PPR-Meta best distinguished viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identified different subsets of the benchmarking data and all tools, except for Sourmash, found unique viral contigs. Tools performance could be improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered. Together, our independent benchmarking provides guidance on choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments for viromics researchers.
Long-Term Oral Tamoxifen Administration Decreases Brain Derived Neurotrophic Factor in the Hippocampus of Female Long-Evans Rats
Authors: Been Laura E. , Halliday Amanda R. , Blossom Sarah M. , Bien Elena M. , Bernhard Anya G. , Roth Grayson E. , Domenech Rosario Karina I. , Pollock Karlie B. , Abramenko Petra E. , Behbehani Leily M. , Pascal Gabriel J. , Kelly Mary Ellen 
Published: April 2023

AbstractTamoxifen is a selective estrogen receptor modulator (SERM) that is commonly used as an adjuvant drug therapy for estrogen receptor-positive breast cancers. While this drug is effective at reducing the rate of cancer recurrence, many patients report unwanted cognitive and affective side effects such as brain fog, confusion, memory impairment, anxiety, and depression. Despite this, the impacts of chronic tamoxifen exposure on the brain are poorly understood, and rodent models of tamoxifen exposure do not replicate the chronic oral administration seen in patients. We therefore used long-termad libconsumption of medicated food pellets in adult female rats to model chronic tamoxifen exposure in a clinically-relevant way. Gonadally-intact adult female Long-Evans Hooded rats consumed tamoxifen medicated food pellets for approximately 12 weeks while control animals received standard chow. At the conclusion of the experiment, animals were euthanized, and blood and brain samples were collected for analyses. Blood tamoxifen levels were measured using a novel ultra-performance liquid chromatography-tandem mass spectrometry assay, which found that this administration paradigm produced serum levels of tamoxifen similar to those in human patients. In the brain, brain derived neurotrophic factor (BDNF) was visualized in the hippocampus using immunohistochemistry and quantified using background-subtracted optical densitometry. Chronic oral tamoxifen treatment resulted in a decrease in BDNF expression across several regions of the hippocampus. Together, these findings provide a novel method of modeling and measuring chronic oral tamoxifen exposure, and suggest a putative mechanism by which tamoxifen may cause cognitive and behavioral changes reported by patients.
Anatomically-specific coupling between innate immune gene repertoire and microbiome structure during coral evolution
Authors: Brown Tanya , Sonett Dylan , McMinds Ryan , Pollock F. Joseph , Medina Mónica , Zaneveld Jesse R. 
Published: April 2023

AbstractTropical reef-building corals exist in intimate symbiosis with diverse microbes and viruses. Coral microbiomes are generally much less diverse than their environment, but across studied corals, the biodiversity of these microbiomes varies greatly. It has previously been hypothesized that differences in coral innate immunity in general, and the copy number of TIR-domain containing innate immune genes in particular, may drive interspecific differences in microbiome structure. Despite many existing studies of coral microbiomes, this hypothesis has previously been difficult to test due to a lack of consistently collected cross-species data on coral microbiomes. In this manuscript, we reannotate TIR-domain containing genes across diverse coral genomes, and use phylogenetic comparative methods to compare these innate immune gene copy numbers against 16S rRNA marker gene data on coral mucus, tissue, and skeleton microbiomes from the Global Coral Microbiome Project (GCMP). The copy number of Toll-like receptor (TLRs) and Interleukin-1 receptor (IL-1Rs) gene families, as well as the total genomic count of their constituent domains (LRR and TIR domains; and Ig and TIR domains, respectively), explained most interspecific differences in microbiome richness and beta-diversity among corals with sequenced genomes. We find that these correlations are also anatomically specific, with an especially strong correlation between IL-1R gene copy numbers and microbiome richness in the coral’s endolithic skeleton. Together, these results suggest innate immunity may play a key role in sculpting microbiome structure in corals.
Improved Quality Metrics for Association and Reproducibility in Chromatin Accessibility Data Using Mutual Information
Authors: Roth Cullen , Venu Vrinda , Job Vanessa , Lubbers Nicholas , Sanbonmatsu Karissa Y. , Steadman Christina R. , Starkenburg Shawn R. 
Published: April 2023

AbstractBackgroundCorrelation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility.ResultsUsing these simulations, we monitored the behavior of several correlation statistics, including the Pearson’sRand Spearman’sρcoefficients as well as Kendall’sτand Top-Down correlation. We also test the behavior of association measures, including the coefficient of determinationR2, Kendall’s W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearman’sρ, Kendall’sτ, and Kendall’s W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, theR2coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships.ConclusionsCollectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.