bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of functional non-coding variants associated with orofacial cleft
Authors: Kumari Priyanka , Friedman Ryan Z. , Pi Lira , Curtis Sarah W. , Paraiso Kitt , Visel Axel , Rhea Lindsey , Dunnwald Martine , Patni Anjali P. , Mar Daniel , Bomsztyk Karol , Mathieu Julie , Ruohola-Baker Hannele , Leslie Elizabeth J. , White Michael A. , Cohen Barak A. , Cornell Robert A. 
Published: June 2024

AbstractOral facial cleft (OFC) is a multifactorial disorder that can present as a cleft lip with or without cleft palate (CL/P) or a cleft palate only. Genome wide association studies (GWAS) of isolated OFC have identified common single nucleotide polymorphisms (SNPs) at the 1q32/IRF6locus and many other loci where, likeIRF6, the presumed OFC-relevant gene is expressed in embryonic oral epithelium. To identify the functional subset of SNPs at eight such loci we conducted a massively parallel reporter assay in a cell line derived from fetal oral epithelium, revealing SNPs with allele-specific effects on enhancer activity. We filtered these against chromatin-mark evidence of enhancers in relevant cell types or tissues, and then tested a subset in traditional reporter assays, yielding six candidates for functional SNPs in five loci (1q32/IRF6, 3q28/TP63, 6p24.3/TFAP2A, 20q12/MAFB, and 9q22.33/FOXE1). We further tested two SNPs nearIRF6and one nearFOXE1by engineering the genome of induced pluripotent stem cells, differentiating the cells into embryonic oral epithelium, and measuring expression ofIRF6orFOXE1and binding of transcription factors; the results strongly supported their candidacy. Conditional analyses of a meta-analysis of GWAS suggest that the two functional SNPs nearIRF6account for the majority of risk for CL/P associated with variation at this locus. This study connects genetic variation associated with orofacial cleft to mechanisms of pathogenesis.
Elucidation of the life cycle of a saprotrophic inoperculate discomycete that is associated with pinesap, using a polyphasic taxonomic approach#
Authors: Demir Özge , Chen Yanpeng , Lambert Christopher , Schüffler Anja , Surup Frank , Stadler Marc 
Published: June 2024

AbstractThis study deals with the elucidation of the life cycle of an inoperculate discomycete that was eventually collected from conifer wood in South Germany and has become famous for the extraordinary diversity of its secondary metabolites when it was studied extensively during the 1990s. It had then been identified asLachnum papyraceum(Lachnaceae,Helotiales) based on morphological traits, and extracts from its mycelial cultures were found to possess extraordinary nematicidal and antibiotic activities. Over 60 different secondary metabolites were finally identified from this fungus after extensive variation of culture media and scale up of production up to 100 litre scale. Among the main active principles were mycorrhizin A and chloromycorrhizin A, which had first been reported in 1987 from an unnamed “mycorrhizal” fungus of the hemiparasitic plant,Monotropa hypopitys(pinesap) that was isolated in Sweden. We noted that both theLachnumstrain and the original mycorrhizin producer were still available in the public domain, and decided to study them for comparison, using a multilocus phylogeny and also generated secondary metabolite profiles of both strains using analytical high performance liquid chromatography coupled to diode array and mass spectrometric detection (HPLC-DAD/MS). Surprisingly, the sequence data as well as the secondary metabolite profiles of both strains were highly similar, and it was also confirmed by phylogenetic methods that the strains are indeed nested within the genusLachnumby comparison of their ITS, LSU and RBP2 sequences. The specimen calledL. papyraceumin the old publications was tentatively re-identified by Hans-Otto Baral asL. cf.subvirgineum,but substantial further work on the taxonomy of the genus remains to be done, anyway. We conclude that someLachnumspecies have a highly complex but all the more interesting life cycle, and the mycorrhizal symbiont partner may invade the host plant, where it may persist as an endophyte and finally turn saprotrophic on the wood of the senescent pine tree. The taxonomy of these fungi should also be further resolved in the future, using a polythetic concept that includes chemotaxonomic data and a multi-locus genealogy.
Stem cell-like memory T cells are closely related to follicular helper T lymphocytes
Authors: Lalinde-Ruiz Nicolás , Padillo-Fino David Santiago , Parra-López Carlos Alberto 
Published: June 2024

AbstractAdoptive cell therapy has the potential to increase antitumor immunity by modifying cellsin-vitroto expand lymphocytes that recognize and attack the tumor. The functional capacity and survival of the cells transferred to the patient heavily depends on the memory subpopulations that are being expanded in the laboratory, hence, obtaining early memory cells is desirable. The main objective of our work was to determine a strategy forin-vitroexpansion of human stem cell-like memory T CD4 lymphocytes. Starting from naive cells, stimulated with a polyclonal agent supplemented with different combinations of cytokines from the common gamma family, we found that the combination of IL-7, IL-15 and IL-21 or IL-7 and IL-21 were the cocktails that produced a greater number of cells with a stem memory phenotype, measured by flow cytometry. Additionally, through the measurement of membrane proteins andin-silicoanalysis, a close relationship between stem cell-like memory and the follicular helper T cells differentiation program was established, which we believe contributes to a better understanding of the processes that underlie the generation and maintenance of memory and, therefore, may improve current strategies of expansion of T cells for immunotherapy purposes.
Cross Tissue DNAm Biomarker Prediction using Transfer Learning
Authors: Mcgreevy Kristen M , Chen Brian H , Horvath Steve , Telesca Donatello 
Published: June 2024

DNA methylation (DNAm) is an epigenetic mechanism vital for regulating gene expression and influencing disease states. Developing accurate DNAm biomarkers often requires data from specific tissues, which are sometimes difficult to access. This study explores the use of Transfer Learning (TL) to predict blood DNAm biomarkers using saliva DNAm data, aiming to overcome limitations posed by sample size and tissue accessibility. We developed TL-based algorithms that integrate DNAm data from multiple tissues. These algorithms were evaluated against traditional Lasso regression and direct saliva DNAm estimates. Our results show that TL significantly improves the prediction accuracy of DNAm biomarkers, outperforming traditional methods in 20 out of 26 biomarkers. We further validated our models using independent datasets, demonstrating that TL-derived predictions reflect known biological relationships, such as sex differences in telomere length and the impact of smoking on DNAm biomarkers. Our findings highlight the potential of TL in enhancing DNAm biomarker prediction across tissues, providing a valuable tool for epigenetic research. The developed algorithms and methodologies are accessible to researchers, fostering advancements in personalized medicine and aging research. This study establishes a framework for utilizing TL to bridge the gap between accessible and pertinent tissue data, paving the way for more accurate and versatile DNAm biomarker applications.ACM Reference FormatKristen M McGreevy, Brian H Chen, Steve Horvath, and Donatello Telesca. 2024. Cross Tissue DNAm Biomarker Prediction using Transfer Learning. 1, 1 (June 2024), 43 pages.https://doi.org/10.1145/nnnnnnn.nnnnnnn
Assessment of false discovery rate control in tandem mass spectrometry analysis using entrapment
Authors: Wen Bo , Freestone Jack , Riffle Michael , MacCoss Michael J. , Noble William S. , Keich Uri 
Published: June 2024

AbstractA pressing statistical challenge in the field of mass spectrometry proteomics is how to assess whether a given software tool provides accurate error control. Each software tool for searching such data uses its own internally implemented methodology for reporting and controlling the error. Many of these software tools are closed source, with incompletely documented methodology, and the strategies for validating the error are inconsistent across tools. In this work, we identify three different methods for validating false discovery rate (FDR) control in use in the field, one of which is invalid, one of which can only provide a lower bound rather than an upper bound, and one of which is valid but under-powered. The result is that the field has a very poor understanding of how well we are doing with respect to FDR control, particularly for the analysis of data-independent acquisition (DIA) data. We therefore propose a theoretical formulation of entrapment experiments that allows us to rigorously characterize the behavior of the various entrapment methods. We also propose a more powerful method for evaluating FDR control, and we employ that method, along with other existing techniques, to characterize a variety of popular search tools. We empirically validate our entrapment analysis in the fairly well-understood DDA setup before applying it in the DIA setup. We find that none of the DIA search tools consistently controls the FDR at the peptide level, and the tools struggle particularly with analysis of single cell datasets.
Next generation AMA1-based plasmids for enhanced heterologous expression in filamentous fungi
Authors: Roux Indra , Woodcraft Clara , Sbaraini Nicolau , Pepper Amy , Wong Emily , Bracegirdle Joe , Chooi Yit-Heng 
Published: June 2024

SummaryEpisomal AMA1-based plasmids are increasingly used for expressing biosynthetic pathways and CRISPR/Cas systems in filamentous fungi cell factories due to their high transformation efficiency and multicopy nature. However, gene expression from AMA1 plasmids has been observed to be highly heterogeneous in growing mycelia. To overcome this limitation, here we developed next-generation AMA1-based plasmids that ensure homogenous and strong expression. We achieved this by evaluating various degradation tags fused to the auxotrophic marker gene on the AMA1 plasmid, which introduces a more stringent selection pressure throughout multicellular fungal growth. With these improved plasmids, we observed inAspergillus nidulansa 5-fold increase in the expression of a fluorescent reporter, a doubling in the efficiency of a CRISPRa system for genome mining, and a up to a 10-fold increase in the production of heterologous natural product metabolites. This strategy has the potential to be applied to diverse filamentous fungi.
Evaluating sustainable feeds for aquaculture by simulating Atlantic salmon lipid metabolism
Authors: Rotnes Filip , Vik Jon Olav , Øyås Ove 
Published: June 2024

AbstractAtlantic salmon aquaculture is an important food source globally, but its sustainability is challenged by environmental impacts and the nutritional demands of farmed fish, particularly when it comes to fatty acids. Salmon feeds still rely heavily on fish or soybean meal, which poses sustainability concerns due to overfishing and carbon footprint. Innovations in feed composition seek to address these challenges, e.g., by using more sustainable ingredients, but the impacts of alternative feeds on fish and environment can be hard to quantify. Here, we developed a model with detailed and flexible accounting for lipids – Simulated Salmon Lipid Metabolism (SimSaLipiM) – to predict the nutritional and environmental outcomes of feed formulations. Integrating SimSaLipiM with feed ingredient databases enabled detailed analysis of anin vivofeed trialin silico. The model predicted optimal feed efficiency in agreement with observations as well as a detailed energy budget and fish biomass lipid composition for each feed. We also used the model to formulate novel sustainable feeds and feed supplements by minimising CO2footprint. Thus, SimSaLipiM makes it easy to identify recipes that optimize key feed properties such as efficiency and environmental impacts. This could be a valuable tool for feed manufacturers, guiding the formulation of feeds that are both sustainable and cost effective. By bridging the gap between feed formulation and the flexible growth and energy requirements of a fish, SimSaLipiM can contribute to advancing sustainable aquaculture.
Human Brain Aging is Associated with Dysregulation of Cell-Type Epigenetic Identity
Authors: Jeong Hyeonsoo , Mendizabal Isabel , Yi Soojin V. 
Published: June 2024

ABSTRACTSignificant links between aging and DNA methylation are emerging from recent studies. On the one hand, DNA methylation undergoes changes with age, a process termed as epigenetic drift. On the other hand, DNA methylation serves as a readily accessible and accurate biomarker for aging. A key missing piece of information, however, is the molecular mechanisms underlying these processes, and how they are related, if any. Addressing the limitations of previous research due to the limited number of investigated CpGs and the heterogeneous nature of tissue samples, here we have examined DNA methylation of over 20 million CpGs across a broad age span in neurons and non-neuronal cells, primarily oligodendrocytes. We show that aging is a primary predictor of DNA methylation variation, surpassing the influence of factors such as sex and schizophrenia diagnosis, among others. On the genome-wide scale, epigenetic drift manifests as significant yet subtle trends that are influenced by the methylation level of individual CpGs. We reveal that CpGs that are highly differentiated between cell types are especially prone to age-associated DNA methylation alterations, leading to the divergence of epigenetic cell type identities as individuals age. On the other hand, CpGs that are included in commonly used epigenetic clocks tend to be those sites that are not highly cell type differentiated. Therefore, dysregulation of epigenetic cell-type identities and current DNA epigenetic clocks represent distinct features of age-associated DNA methylation alterations.
Comprehensive profiling of genomic invertons in defined gut microbial community reveals associations with intestinal colonization and surface adhesion
Authors: Jin Xiaofan , Cheng Alice G. , Chanin Rachael , Yu Feiqiao B. , Dimas Alejandra , Jasper Marissa , Weakley Allison , Yan Jia , Bhatt Ami S. , Pollard Katherine S. 
Published: June 2024

AbstractBacteria use invertible genetic elements known as invertons to generate heterogeneity amongst a population and adapt to new and changing environments. In human gut bacteria, invertons are often found near genes associated with cell surface modifications, suggesting key roles in modulating dynamic processes such as surface adhesion and intestinal colonization. However, comprehensive testing of this hypothesis across complex bacterial communities like the human gut microbiome remains challenging. Metagenomic sequencing holds promising for detecting inversions without isolation and culturing, but ambiguity in read alignment limits the accuracy of the result-ing inverton predictions. Here, we developed a customized bioinformatic workflow – PhaseFinderDC – to identify and track invertons in metagenomic data. Applying this method to a defined yet complex gut community (hCom2) across different growth environments over time using bothin vitroandin vivometagenomic samples, we detected invertons in most hCom2 strains. These include invertons whose orientation probabilities change over time and are statistically associated with environmental conditions. We used motif enrichment to identify putative inverton promoters and predict genes regulated by inverton flipping during intestinal colonization and surface adhesion. Analysis of inverton-proximal genes also revealed candidate invertases that may regulate flipping of specific invertons. Collectively, these findings suggest that surface adhesion and intestinal colonization in complex gut communities directly modulate inverton dynamics, offering new insights into the genetic mechanisms underlying these processes.
Discovery of Potent Degraders of the Dengue Virus Envelope Protein
Authors: Li Zhengnian , Liu Han-Yuan , He Zhixiang , Chakravarty Antara , Golden Ryan P. , Jiang Zixuan , You Inchul , Yue Hong , Donovan Katherine A. , Du Guangyan , Che Jianwei , Tse Jason , Che Isaac , Lu Wenchao , Fischer Eric S. , Zhang Tinghu , Gray Nathanael S. , Yang Priscilla L. 
Published: June 2024

AbstractTargeted protein degradation has been widely adopted as a new approach to eliminate both established and previously recalcitrant therapeutic targets. Here we report the development of small molecule degraders of the envelope (E) protein of dengue virus. We developed two classes of bivalent E-degraders, linking two previously reported E-binding small molecules, GNF-2 and CVM-2-12-2, to a glutarimide-based recruiter of the CRL4CRBNligase to effect proteosome-mediated degradation of the E protein. ZXH-2-107 (based on GNF-2) is an E degrader with ABL inhibition while ZXH-8-004 (based on CVM-2-12-2) is a selective and potent E-degrader. These two compounds provide proof-of-concept that difficult-to-drug targets such as a viral envelope protein can be effectively eliminated using a bivalent degrader and provide starting points for the future development of a new class antiviral drugs.
Assessing the efficiency and heritability of blocked tree breeding trials
Authors: Piepho Hans-Peter , Williams Emlyn , Prus Maryna 
Published: June 2024

AbstractProgeny trials in tree breeding are often laid out using blocked experimental designs, in which families are randomly assigned to plots and several trees are planted per plot. Such designs are optimized for the assessment of family effects. However, tree breeders are primarily interested in assessing breeding values of individual trees. This paper considers the assessment of heritability at both the family and tree levels. We assess heritability based on pairwise comparisons among individual trees. The approach shows that there is considerable heterogeneity in pairwise heritabilities, primarily due to the differences in both genetic as well as error variances among within- and between-family comparisons. Our results further show that efficient blocking positively affects all types of comparison except those among trees within the same plot.
Estimating the historical impact of outbreak response immunization programs across 210 outbreaks in LMICs
Authors: Delport D. , Muellenmeister A.M. , MacKechnie G. , Vaccher S. , Mengistu T. , Hogan D. , Abeysuriya R.G. , Scott N. 
Published: June 2024

BackgroundOutbreaks of vaccine-preventable diseases continue to occur in low- and middle-income countries (LMICs), requiring outbreak response immunization (ORI) programs for containment. To inform future investment decisions, this study aimed to estimate the cases, deaths, disability-adjusted life years (DALYs), and societal economic costs averted by past ORI programs. Outbreaks of measles, Ebola, yellow fever, cholera, and meningococcal meningitis in LMICs between 2000-2023 were considered.Methods210 outbreaks (51 measles, 40 cholera, 88 yellow fever, 24 meningitis, 7 Ebola) were identified with sufficient data for analysis. Agent-based models were calibrated for each disease such that after controlling for baseline vaccine coverage, ORI initiation time, speed of vaccine delivery, environmental variables, or endemic prevalence of the disease, observed outbreaks were within the distribution of simulated outbreaks. A status-quo and no ORI scenario were compared for each outbreak.FindingsAcross 210 outbreaks, ORI programs are estimated to have averted 5·81M [95% uncertainty interval 5·75M–5·87M] cases (4·01M measles, 283K cholera, 1·50M yellow fever, 21·3K meningitis, 820 Ebola), 327K [317K–338K] deaths (20.0K measles, 5215 cholera, 300K yellow fever, 1599 meningitis, 381 Ebola), 14·6M [14·1M–15·1M] DALYs (1·27M measles, 220K cholera, 13·0M yellow fever, 113K meningitis, 16·6K Ebola), and US$31·7B [29·0B–34·9B] (US$710M measles, US$156M cholera, US$30·7B yellow fever, US$97·6M meningitis, US$6·72M Ebola) in societal economic costs. In general, the more rapidly the ORI was initiated the greater the impact.InterpretationORI programs are critical for reducing the health and economic impacts of outbreaks of vaccine-preventable diseases.FundingGavi,the Vaccine Alliance.
Ethnoracial Disparities in Breast Cancer Treatment Time and Survival: A Systematic Review With a DAG-based Causal Model
Authors: Hesari Parisa M. , James Drexler , Lizotte Daniel J. , Bauer Greta R. 
Published: June 2024

AbstractFor interventions aimed at redressing health disparities in breast cancer to be effective, a clear understanding of the nature and causes of these disparities is required. Our question is: what is the current evidence for ethnoracial disparities in time-to-treatment initiation and survival in breast cancer, and how are the causal mechanisms of these disparities conceptualized in the literature? A comprehensive systematic search of studies on cohorts of female breast cancer patients diagnosed with stage I-III was performed. Directed acyclic graphs were used to describe implicit causal relationships between ethnoracial group membership and time-to-treatment initiation and survival outcomes. This review revealed strong evidence for ethnoracial disparities in both time to treatment and survival among breast cancer patients. Unmeasured factors identified by the authors highlighted gaps in data sources and opportunities for causal reasoning. While the existing literature describes ethnoracial disparities, there is very limited discussion of causal mechanisms, and no discussion of system-level rather than individual-level effects. In response, a biosocioecological model of breast cancer disparity was developed to integrate system-level considerations into future research. Addressing established ethnoracial disparities in breast cancer requires new research that explicitly considers the causal mechanisms of potential interventions, incorporating unmeasured factors contributing to these disparities.