bluuebunny/crossref_metadata_2025_split huggingface dataset:
A preliminary assessment of the genome sequence of the Annual Mercury,Mercurialis annua
Authors: Dwivedi Mratunjay , Vijay Nagarjun 
Published: June 2024

SummaryReview of Christenhusz et al., Wellcome Open Research. A high-quality genome sequence of the Annual Mercury,Mercurialis annuais generated as part of the Darwin Tree of Life Project. The Annual Mercury plant is a good study system for evolutionary transitions between sexual systems, mechanisms of sex determination in plants and changes in ploidy level. The XX female sequenced in this study provides a chromosome-level assembly with reasonable contiguity and high gene completeness. We compare the gene completeness of the assembly presented with those of closely related species, including another published assembly of the Annual Mercury generated using a polyploid individual. Annotation and comparative analysis of the organelle genomes suggest complete circular assemblies. However, we note that the NCBI submissions are tagged as linear. The repeat content identified on the autosomes and X chromosome appears comparable, suggesting the sex chromosomes are relatively recent. An alternative possibility is that our preliminary analysis failed to identify repeats unique to the X chromosome or that these repeat regions have not been assembled in the genome. The harder-to-assemble centromere and telomere regions are not annotated in the genome and are potentially incomplete or missing. We identify putative centromere regions with elevated GC content, but they must be validated. The demographic histories reconstructed for the autosomes and X suggest distinct trajectories irrespective of the scaling parameters. Compared to the autosomes, the older histories recorded on the X are a promising avenue for further work to study the origin of the sex chromosome. Our preliminary assessment of the genome sequence suggests the genome is of sufficiently good quality for use as a reference for diverse analysis aimed at answering important eco-evolutionary questions of interest that can be answered using this system.
Mitochondrial Dynamics and Bioenergetics in iPSC-Derived Neurons with Familial Alzheimer’s Disease Mutations
Authors: MacMullen Courtney , Sharma Neelam , Davis Ronald L. 
Published: June 2024

SummaryMitochondrial (MT) dysfunction is a hallmark of Alzheimer’s Disease (AD), but the specific defects across forms of AD are unknown. We measured multiple parameters of MT dynamics and function, and neurite degeneration, in iPSC-derived human neurons possessing natural and engineered mutations in PS1, PS2, and APP genes. Mutations in all three genes altered MT function measured by basal, ATP-linked, and maximal oxygen consumption rate; and spare respiratory capacity, with PS1/PS2 alleles being more severe than APP mutations. Electron flow through Complexes I-IV was decreased in PS1/PS2 mutations but; in contrast, APP alleles had only modest impairments of CI and CII. We measured aspects of MT dynamics including fragmentation, and neurite degeneration, both of which were dramatic in PS1/PS2 alleles, but essentially absent in APP alleles. The marked differences in MT pathology may occur from the distinct ways APP is processed into Aβ and may correlate with the disease severity.
PIP-Seq identifies novel heterogeneous lung innate lymphocyte population activation after combustion product exposure
Authors: Huang Yung-An , Wang Xinyu , Kim Jong-Chan , Yao Xiang , Sethi Anshika , Strohm Allyssa , Doherty Taylor A. 
Published: June 2024

AbstractInnate lymphoid cells (ILCs) are a heterogeneous population that play diverse roles in airway inflammation after exposure to allergens and infections. However, how ILCs respond after exposure to environmental toxins is not well understood. Here we show a novel method for studying the heterogeneity of rare lung ILC populations by magnetic enrichment for lung ILCs followed by particle-templated instant partition sequencing (PIP-seq). Using this method, we were able to identify novel group 1 and group 2 ILC subsets that exist after exposure to both fungal allergen and burn pit-related constituents (BPC) that include dioxin, aromatic hydrocarbon, and particulate matter. Toxin exposure in combination with fungal allergen induced activation of specific ILC1/NK and ILC2 populations as well as promoted neutrophilic lung inflammation. Oxidative stress pathways and downregulation of specific ribosomal protein genes (Rpl41andRps19) implicated in anti-inflammatory responses were present after BPC exposure. Increased IFNγ expression and other pro-neutrophilic mediator transcripts were increased in BPC-stimulated lung innate lymphoid cells. Further, the addition of BPC inducedHspa8(encodes HSC70) and aryl hydrocarbon transcription factor activity across multiple lung ILC subsets. Overall, using an airway disease model that develops after occupational and environmental exposures, we demonstrate an effective method to better understand heterogenous ILC subset activation.
Comparative analysis of muscle thickness, muscle percentage of subcutaneous tissue, and muscle luminance in skeletal muscles of limbs of normal children and children with limb disabilities due to cerebral palsy using ultrasound imaging
Authors: Ishikura Hideki 
Published: June 2024

AbstractBackgroundUltrasound imaging is increasingly utilized for musculoskeletal evaluation because it is cost-effective and non-invasive. This study aims to analyze the differences in muscle thickness, muscle percentage of subcutaneous tissue, and muscle luminance in children with limb disabilities due to cerebral palsy compared with typically developing children.MethodsThis cross-sectional study included 12 children aged 6–15 years, divided equally into two groups: children with physical disabilities due to cerebral palsy and healthy controls. Ultrasound imaging was used to measure muscle thickness, percentage of muscle in subcutaneous tissue, and muscle luminance in various muscle groups of the limbs. Statistical analyses were conducted using t-tests to compare the two groups.ResultsSignificant differences were observed in muscle thickness and percentage of muscle in subcutaneous tissue between the groups, particularly in the lower limbs. Muscle luminance did not exhibit consistent differences. These findings suggest a decreased muscle mass and altered composition in children with cerebral palsy, which may influence their physical function and mobility.ConclusionsOur results underscore the value of ultrasound in clinically assessing muscle properties in children with cerebral palsy. This modality offers a promising tool for evaluating muscle alterations and potentially guiding targeted interventions to improve mobility and quality of life in affected children.
Deep Learning-Based High-Throughput Phenotyping Of Maize (Zea maysL.) Tasseling From Uas Imagery Across Environments
Authors: Shepard Nicholas R. , DeSalvio Aaron J. , Arik Mustafa , Adak Alper , Murray Seth C. , Varela Jose Ignacio , de Leon Natalia 
Published: June 2024

AbstractFlowering time is a critical phenological trait in maize (Zea maysL.) breeding programs. Traditional measurements for assessing flowering time involve semi-subjective and labor-intensive manual observation, limiting the scale and efficiency of genetics and breeding improvement. Leveraging unoccupied aerial system (UAS, also known as UAVs or drones) technology coupled with convolutional neural networks (CNNs) presents a promising approach for high-throughput phenotyping of tasseling in maize. Most CNN image analysis is overly complicated for simple tasks relevant to plant scientists. Here a methodology for extracting tasseling from RGB imagery using a CNN-based approach was applied to 220 hybrids and 30 test lines grown in eight diverse environments (Wisconsin and Texas, U.S.A.) then validated through an unrelated set of hybrids. Overall accuracies of .946, .911, .985, and .988 were obtained for classifying maize images with or without tassels from College Station, TX in 2020; College Station, TX in 2021; Arlington, WI in 2021; and Madison, WI in 2021 respectively. By employing deep learning techniques, larger volumes of phenotypic data can be processed enabling high-throughput phenotyping in breeding programs. Although large datasets are required to train CNN models, the proposed methodology prioritizes simplicity in computational architecture while maintaining effectiveness in identifying flowered maize across diverse genotypes and environments.
PlantRNA-FM: An Interpretable RNA Foundation Model for Exploration Functional RNA Motifs in Plants
Authors: Yu Haopeng , Yang Heng , Sun Wenqing , Yan Zongyun , Yang Xiaofei , Zhang Huakun , Ding Yiliang , Li Ke 
Published: June 2024

ABSTRACTThe complex ‘language’ of plant RNA encodes a vast array of biological regulatory elements that orchestrate crucial aspects of plant growth, development, and adaptation to environmental stresses. Recent advancements in foundation models (FMs) have demonstrated their unprecedented potential to decipher complex ‘language’ in biology. In this study, we introduced PlantRNA-FM, a novel high-performance and interpretable RNA FM specifically designed based on RNA features including both sequence and structure. PlantRNA-FM was pre-trained on an extensive dataset, integrating RNA sequences and RNA structure information from 1,124 distinct plant species. PlantRNA-FM exhibits superior performance in plant-specific downstream tasks, such as plant RNA annotation prediction and RNA translation efficiency (TE) prediction. Compared to the second-best FMs, PlantRNA-FM achieved anF1 score improvement of up to 52.45% in RNA genic region annotation prediction and up to 15.30% in translation efficiency prediction, respectively. Our PlantRNA-FM is empowered by our interpretable framework that facilitates the identification of biologically functional RNA sequence and structure motifs, including both RNA secondary and tertiary structure motifs across transcriptomes. Through experimental validations, we revealed novel translation-associated RNA motifs in plants. Our PlantRNA-FM also highlighted the importance of the position information of these functional RNA motifs in genic regions. Taken together, our PlantRNA-FM facilitates the exploration of functional RNA motifs across the complexity of transcriptomes, empowering plant scientists with novel capabilities for programming RNA codes in plants.
Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits
Authors: Zhu Tao , Xia Chunjiao , Yu Ranran , Zhou Xinkai , Xu Xingbing , Wang Lin , Zong Zhanxiang , Yang Junjiao , Liu Yinmeng , Ming Luchang , You Yuxin , Chen Dijun , Xie Weibo 
Published: June 2024

AbstractUnraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for ∼15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function ofOsbZIP06in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.
Hypothalamic prostaglandins facilitate recovery from hypoglycemia but exacerbate recurrent hypoglycemia in mice
Authors: Abe Takashi , Xu Shucheng , Sugiura Yuki , Arima Yuichiro , Hayasaka Takahiro , Lee Ming-Liang , Ishimoto Taiga , Araki Yudai , Ngurari Samson , Niu Ziwei , Iijima Norifumi , Diano Sabrina , Toda Chitoku 
Published: June 2024

AbstractThe hypothalamus monitors blood glucose levels and regulates glucose production in the liver. In response to hypoglycemia, glucose-inhibited (GI) neurons trigger counter-regulatory responses (CRRs), which stimulate the release of glucagon, epinephrine, and cortisol to elevate blood glucose. Recurrent hypoglycemia (RH), however, reduces the effectiveness of these CRRs. This study examined the role of hypothalamic prostaglandins in glucose recovery during acute hypoglycemia and RH. Using imaging mass spectrometry and liquid chromatography/mass spectrometry, phospholipid and prostaglandin levels in the hypothalamus of C57BL mice were increased following insulin or 2-deoxy-glucose administration. Ibuprofen, a nonsteroidal anti-inflammatory drug (NSAID), was infused into the ventromedial hypothalamus (VMH) to analyze its effect on glucose production during hypoglycemia, revealing that prostaglandin inhibition decreased glucagon secretion. Additionally, RH-treated mice decreased glucagon release and glucose production during hypoglycemia. Inhibiting prostaglandin production via short-hairpin RNA against cytosolic phospholipase A2 (cPLA2) in the hypothalamus restored CRRs diminished by RH via increasing glucagon sensitivity. These findings suggest that hypothalamic prostaglandins play a critical role in glucose recovery from acute hypoglycemia by activating VMH neurons and are also crucial for the attenuation of CRRs during RH.Graphical AbstractArticle HighlightsInsulin decreases arachidonic acid-containing phospholipids and increases prostaglandin production in the hypothalamus.Prostaglandin in the hypothalamus increases glucagon secretion and glucose production during hypoglycemia.Recurrent hypoglycemia decreases glucagon secretion and glucose production during hypoglycemia.Prostaglandin in the hypothalamus during recurrent hypoglycemia decreases glucagon sensitivity and glucose production.
Exact switching time distributions for autoregulated gene expression models with mRNA and protein descriptions
Authors: Liu Shan , Wu Bingjie , Jia Chen 
Published: June 2024

AbstractIn this study, we obtain the exact switching time distributions between the free and bound gene states for a detailed stochastic model of an autoregulatory genetic feedback loop with transcription, translation, mRNA and protein decay, as well as protein-gene interactions. The analytical solution generalizes and corrects the previous ones obtained in [Phys. Rev. Lett. 101, 118104 (2008)] and [Nat. Commun. 9, 3305 (2018)] for a reduced model of an autoregulatory loop that ignores the mRNA dynamics. We find that when the mRNA dynamics is modelled explicitly, the holding time in the free gene state can produce three shapes of steady-state distributions (decaying, bell-shaped, and bimodal). In particular, the detailed model with both mRNA and protein descriptions can produce a distribution shape that the reduced model fails to capture — the detailed model of a negative (positive) feedback loop can display a bimodal (bell-shaped) holding time distribution, while the reduced model cannot. Interestingly, we also find that an autoregulatory loop can produce a heavy-tailed holding time distribution and the origin of this heavy-tailed phenomenon is clarified using our analytical solution. Finally, we investigate how the distribution shape is affected by the type of feedback, the binding and unbinding rates, and the transcription rates.
Insect metamorphosis is regulated differently between sexes by members of a microRNA cluster
Authors: Li Chade , Chan Ki Kei , Nong Wenyan , Chen ShanShan , So Wai Lok , Qu Zhe , Wu Heidi Y.C. , Yip Ho Yin , Chan Chi Bun , Tobe Stephen S. , Bendena William G. , Kai Zhen Peng , Hui Jerome H.L. 
Published: June 2024

AbstractInsects comprise the majority of all described animal species and dominate the terrestrial habitats. The evolution of insect metamorphosis played a profound role in their successful adaptation and radiation. Insect metamorphosis is dependent on hormones ecdysteroids and sesquiterpenoids such as juvenile hormone. Despite the fact there are genuine differences between sexes during insect metamorphosis which facilitate their successful mating, how such sexual dimorphism in metamorphosis is being controlled is poorly known. We first generated transcriptomic profiles of male and female flies in late larvae and early pupae stages. Using a combination of genome-wide prediction andin vitrodual-luciferase validations, members of a microRNA cluster miR-277/34 were found to potentially regulate the neuropeptide receptor (AstC-R1) that when activated inhibits the sesquiterpenoid pathway and a juvenile hormone-dependent transcription factor (Kr-h1) in flyDrosophila melanogaster.Loss-of-function mutants were created deleting either miR-277 or miR-34, and expression levels of bothAstC-R1andKr-h1as well as ecdysteroid and sesquiterpenoid hormone titres were altered. Further comparison of transcriptomes of the late larvae and early pupae of both sexes revealed differential gene pathways being regulated by members of miR-277/34 between sexes during metamorphosis. This study highlights how members of a microRNA cluster control hormonal and developmental gene pathways in different sexes of insects during metamorphosis.
Structural and mechanistic insights intoPlasmodiumeIF2alpha dephosphorylation by UIS2 during the erythrocytic stage
Authors: Wu Su , Wagner Gerhard 
Published: June 2024

AbstractUIS2 is a promising therapeutic target for malaria due to its essential role in the transmission and infectivity ofPlasmodiumto the host hepatocytes. InPlasmodium, UIS2 acts as a phosphatase toward phosphorylated eIF2alpha at Ser59, regulating translation initiation. However, its role during the erythrocytic stage, which causes clinical symptoms, remains unclear, and its protein structure for elucidating the dephosphorylation mechanism is unavailable. In this study, we analyzed thePlasmodiumphenotype screening database and found thatUIS2-deficientPlasmodiumfails to proliferate during the erythrocytic stages. Single-cell transcriptomic data from the Malaria Cell Atlas revealedUIS2expression during both hepatic and erythrocytic stages, with significant upregulation in trophozoites and late schizonts, suggesting UIS2’s essential role in erythrocytic stage development. Structural analyses using AlphaFold modeling demonstrated that the UIS2 phosphatase domain (UIS2-PD) shares homology with human purple acid phosphatase, featuring conserved catalytic site residues. We observed that the N-terminal domain of UIS2 interacts with the S1 domain loop of a phospho-mimic mutant (Ser59Asp) eIF2alpha via electrostatic interactions. This protein interaction is distal to the phosphatase domain, indicating a unique substrate recruitment mechanism distinct from mammalian serine/threonine phosphatase PP1. Additionally, we identified a negatively charged cavity in UIS2-PD capable of binding the Ser59-containing loop in eIF2alpha for substrate recognition. Molecular docking studies showed that the phosphatase inhibitor salubrinal binds to this negatively charged cavity, potentially obstructing enzyme-substrate interactions. These structural insights into UIS2 and its interaction with eIF2alpha provide promising avenues for developing novel antimalarial drugs.Significance StatementMalaria poses a significant global health challenge, particularly with rising resistance to artemisinin therapies. This study reveals the critical role of UIS2 inPlasmodiumproliferation during the symptomatic blood stage through phenotype screening and single-cell transcriptomics. We characterized the catalytic site within UIS2-PD and discovered a surface cavity for recognizing phosphorylated eIF2alpha by UIS2-PD, which can be inhibited by small molecules. Our findings identify UIS2 as a promising target for new antimalarial drugs, addressing both blood-stage parasites to alleviate clinical symptoms and liver-stage parasites for prophylactic treatment. This dual targeting strategy could prevent malaria onset post-exposure and reduce the overall parasite burden. The protein interaction between UIS2 and eIF2alpha is chemically targetable, facilitating the development of effective UIS2 inhibitors.
In silicoscreening identifies SHPRH as a novel nucleosome acidic patch interactor
Authors: James Allison M. , Schmid Ernst W. , Walter Johannes C. , Farnung Lucas 
Published: June 2024

Nucleosomes are the fundamental unit of eukaryotic chromatin. Diverse factors interact with nucleosomes to modulate chromatin architecture and facilitate DNA repair, replication, transcription, and other cellular processes. An important platform for chromatin binding is the H2A–H2B acidic patch. Here, we used AlphaFold-Multimer to screen over 7000 human proteins for nucleosomal acidic patch binding and identify 41 potential acidic patch binders. We determined the cryo-EM structure of one hit, SHPRH, with the nucleosome at 2.8 Å. The structure confirms the predicted acidic patch interaction, reveals that the SHPRH ATPase engages a different nucleosomal DNA location than other SF2-type ATPases, and clarifies the roles of SHPRH’s domains in nucleosome recognition. Our results illustrate the use ofin silicoscreening as a high throughput method to identify specific interaction types and expands the set of potential acidic patch binding factors.All the screening data is freely available athttps://predictomes.org/view/acidicpatch
Fitbit-measured physical activity is inversely associated with incident atrial fibrillation among All of Us participants
Authors: Barua Souptik , Upadhyay Dhairya , Surapaneni Aditya , Grams Morgan , Jankelson Lior , Heffron Sean 
Published: June 2024

ABSTRACTBackground and AimsIndividuals who report meeting weekly moderate to vigorous physical activity (MVPA) guidelines have lower risk of atrial fibrillation (AF). However existing studies have relied on subjective questionnaires or short-duration (<1 week) objective assessments using accelerometry. The objective of this research was to investigate an association between moderate to vigorous physical activity (MVPA) levels and the incidence of atrial fibrillation (AF), utilizing long-term, free-living accelerometry data.Methods1-year Fitbit data, in addition to survey and electronic health record (EHR) data, were extracted from the NIHAll of Us(AoU) research database. Cox proportional hazards regression was used to model the association of average MVPA (both continuous and categorized as <30, 30-150,151-300, and >300 minutes/week) and incident AF over a five-year follow-up period.Results6086 AoU participants were included (51±16 years, 70% female, 83% White, BMI 28.5±4.9 kg/m2, 41±12 complete weeks of Fitbit wear). 55 individuals (0.9%) experienced incident AF in the five-year follow-up period. More time spent in MVPA was associated with lower AF risk (HR = 0.89 [0.81,0.98], p=0.02), with a step-wise reduction for 151-300 mins (p=0.07) and >300 mins (p=0.04) of weekly MVPA, respectively. In a subset of 3847 participants with genomic data, this association persisted after adjustment for AF genetic risk score.ConclusionsHigher amounts of objectively measured MVPA, measured using free-living, long-term accelerometry data, were inversely associated with risk of incident AF, independent of clinical and genetic risk factors.