bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation Model
Authors: Fang Chen , Hu Zhilong , Chang Shaole , Long Qingqing , Cui Wentao , Liu Wenhao , Li Cong , Liu Yana , Wang Pengfei , Meng Zhen , Pan Jia , Zhou Yuanchun , Feng Guihai , Chen Linghui , Li Xin 
Published: June 2024

AbstractInspired by the advancements in pre-trained Large Language Models, there has been a surge of studies in the Life Sciences focusing on constructing foundation models with large scale single-cell RNA-seq data. These studies typically involve pre-training a transformer model on large-scale single-cell sequencing data, followed by fine-tuning for a variety of downstream tasks, achieving notable performance. However, these models all share a common short-coming: to utilize the transformer architecture, originally designed for textual data, they artificially impose a sequential structure on genes within cells, simplifying the complex interactions between genes. Furthermore, they focus solely on transcriptomic data, neglecting other relevant biological information. To address these issues, here we introduce Cell-Graph Compass (CGC), the first foundational model that leverages graph structures to model single cells and describes cells from multiple perspectives, including transcriptional profiles, gene text summaries, transcription factor regulatory networks, gene co-expression patterns, and gene positional relationships. By incorporating self-attention mechanisms, we pretrained the model on 50 million human single-cell sequencing data, resulting in a robust digital representation of cells. Extensive downstream experiments demonstrate that our approach can capture meaningful biological knowledge and achieve superior results in various problem scenarios, achieving the state-of-the-art (SOTA).
Expression of a single inhibitory member of the Ly49 receptor family is sufficient to license NK cells for effector functions
Authors: Piersma Sytse J. , Li Shasha , Wong Pamela , Bern Michael D. , Poursine-Laurent Jennifer , Yang Liping , Beckman Diana L. , Parikh Bijal A. , Yokoyama Wayne M. 
Published: June 2024

AbstractNatural killer (NK) cells recognize target cells through germline-encoded activation and inhibitory receptors enabling effective immunity against viruses and cancer. The Ly49 receptor family in the mouse and killer immunoglobin-like receptor family in humans play a central role in NK cell immunity through recognition of MHC class I and related molecules. Functionally, these receptor families are involved in licensing and rejection of MHC-I-deficient cells through missing-self. The Ly49 family is highly polymorphic, making it challenging to detail the contributions of individual Ly49 receptors to NK cell function. Herein, we showed mice lacking expression of all Ly49s were unable to reject missing-self target cellsin vivo, were defective in NK cell licensing, and displayed lower KLRG1 on the surface of NK cells. Expression of Ly49A alone on a H-2Ddbackground restored missing-self target cell rejection, NK cell licensing, and NK cell KLRG1 expression. Thus, a single inhibitory Ly49 receptor is sufficient to license NK cells and mediate missing-selfin vivo.
Bbl1 Allele of the Receptor Kinase Subfamily VII PBL38 Is Required for Elongated Root Hairs in Arabidopsis
Authors: Kohorn Bruce D. 
Published: June 2024

AbstractIn a screen for mutations that alter cell morphology and adhesion as a marker for cell wall composition alterations, an Arabidopsis seedling with root hairs that fail to elongate was identified. Root hairs are rounded and bubble-like, and the mutation was named Bubbles or bbl1. No other visible whole plant phenotypes were observed. Using backcrosses with wild type, and genomic sequencing of pooled F2 individuals with the Bubbles phenotype, 14 candidates for the mutant allele were identified. T-DNA alleles of one of these candidates showed a similar but partial phenotype to bbl1, and indicate that bbl1 is an allele of AT2G39110 previously identified as PBL38 (AvrPphB SUSCEPTIBLE1-LIKE38), a member of receptor kinase subfamily VII. PBL38 has been associated with the response to pathogens. bbl1 is a point mutation that causes a Glutamic acid to Lysine change at position 140, and is complimented by a C-terminal GFP fusion to the coding region of AT2G39110, indicating that the BBL1 gene (PBL38) is involved in correct root hair formation. AT2G39110 is expressed only in roots early in seedling maturation, and the GFP fusion protein localizes to the cell surface, consistent with the prediction that the gene encodes a receptor-like protein kinase. In bbl1 root hairs, the actin cytoskeleton does not form, while in bbl1 roots and other tissues normal actin cytoskeleton is observed.
Robust parameter estimation and identifiability analysis with Hybrid Neural Ordinary Differential Equations in Computational Biology
Authors: Giampiccolo Stefano , Reali Federico , Fochesato Anna , Iacca Giovanni , Marchetti Luca 
Published: June 2024

AbstractParameter estimation is one of the central problems in computational modeling of biological systems. Typically, scientists must fully specify the mathematical structure of the model, often expressed as a system of ordinary differential equations, to estimate the parameters. This process poses significant challenges due to the necessity for a detailed understanding of the underlying biological mechanisms. In this paper, we present an approach for estimating model parameters and assessing their identifiability in situations where only partial knowledge of the system structure is available. The partially known model is extended into a system of Hybrid Neural Ordinary Differential Equations, which captures the unknown portions of the system using neural networks.Integrating neural networks into the model structure introduces two primary challenges for parameter estimation: the need to globally explore the search space while employing gradient-based optimization, and the assessment of parameter identifiability, which may be hindered by the expressive nature of neural networks. To overcome the first issue, we treat biological parameters as hyperparameters in the extended model, exploring the parameter search space during hyperparameter tuning. The second issue is then addressed by ana posteriorianalysis of parameter identifiability, computed by introducing a variant of a well-established approach for mechanistic models. These two components are integrated into an end-to-end pipeline that is thoroughly described in the paper. We assess the effectiveness of the proposed workflow on test cases derived from three different benchmark models. These test cases have been designed to mimic real-world conditions, including the presence of noise in the training data and various levels of data availability for the system variables.Author summaryParameter estimation is a central challenge in modeling biological systems. Typically, scientists calibrate the parameters by aligning model predictions with measured data once the model structure is defined. Our paper introduces a workflow that leverages the integration between mechanistic modeling and machine learning to estimate model parameters when the model structure is not fully known. We focus mainly on analyzing the identifiability of the model parameters, which measures how confident we can be in the parameter estimates given the available experimental data and partial mechanistic understanding of the system. We assessed the effectiveness of our approach in variousin silicoscenarios. Our workflow represents a first step to adapting traditional methods used in fully mechanistic models to the scenario of hybrid modeling.
Practical considerations regarding estimatingNewhen generations overlap
Authors: Waples Robin S. 
Published: June 2024

AbstractResearchers studying species in nature often find it challenging to apply methods based on simplistic models of reality. Here I consider how some real-world complications influence demographic estimates of effective population size (Ne) when generations overlap. The most widely-used model (by Hill) expressesNeas a function of variance in lifetime reproductive output (LRO) of theN1members of a newborn cohort. Hill’s model assumes stable age structure and constant population size, in which case mean. In real-world applications, researchers often ask whether unbiased estimates can be obtained under the following conditions: (1) Whenfor empirical data; (2) If cohorts are defined at a later age than newborns; (3) If survival to age at sexual maturity (α) is not random; (4) When some or all null parents (those withLRO=0) are not sampled. Using analytical methods and computer simulations, I show that: (1) Because variance in offspring number is positively correlated with the mean,will be biased using raw data when, but this bias can be overcome by rescaling var(LRO) to its expected value when. (2) The cohort can be defined at any age ≤α, provided that (a)LROdata cover the full lifespan (e.g., production of newborns by newborns, or production of adults by adults), and (b) survival to age α is random. (3) If juvenile survival is family-correlated, defining cohorts at age α avoids upward bias inthat occurs if newborn cohorts are used. (4) Missing some or all null parents has no effect on, provided that data are rescaled to.
Developing epidemiological preparedness for a plant disease invasion: modelling citrus huánglóngbìng in the European Union
Authors: Ellis John , Lázaro Elena , Duarte Beatriz , Magalhães Tomás , Duarte Amílcar , Benhadi-Marín Jacinto , Pereira José Alberto , Vicent Antonio , Parnell Stephen , Cunniffe Nik J. 
Published: June 2024

AbstractHuánglóngbíng (HLB; citrus greening) is the most damaging disease of citrus worldwide. While citrus production in the USA and Brazil have been affected for decades, HLB has not been detected in the European Union (EU). However, psyllid vectors have already invaded and spread in Portugal and Spain, and in 2023 the psyllid species known to vector HLB in the Americas was first reported within the EU. We develop a landscape-scale, epidemiological model, accounting for heterogeneous citrus cultivation and vector dispersal, as well as climate and disease management. We use our model to predict HLB dynamics following introduction into high-density citrus areas in Spain, assessing detection and control strategies. Even with significant visual surveillance, we predict any epidemic will be widespread on first detection, with eradication unlikely. Introducing increased inspection and roguing following first detection, particularly if coupled with intensive insecticide use, could potentially sustain citrus production for some time. However, this may require chemical application rates that are not permissible in the EU. Disease management strategies targeting asymptomatic infection will likely lead to more successful outcomes. Our work highlights modelling as a key component of developing epidemiological preparedness for a pathogen invasion that is, at least somewhat, predictable in advance.
Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer
Authors: Plubell Deanna L , Remes Philip M. , Wu Christine C. , Jacob Cristina C. , Merrihew Gennifer E. , Hsu Chris , Shulman Nick , MacLean Brendan X. , Heil Lilian , Poston Kathleen , Montine Tom , MacCoss Michael J. 
Published: June 2024

ABSTRACTThe development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the StellarTMmass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.
Metabolic activities are selective modulators for individual segmentation clock processes
Authors: Matsuda Mitsuhiro , Lázaro Jorge , Ebisuya Miki 
Published: June 2024

AbstractA sequence of cellular and molecular processes unfolding during embryonic development prompts fundamental questions of how the tempo of multiple processes is coordinated and whether a common global modulator exists. The oscillation of the segmentation clock is a well-studied model of developmental tempo. While the clock period is known to scale with the kinetics of gene expression and degradation processes of the core clock gene Hes7 across mammalian species, how these key molecular processes are coordinated remains unclear. In this study, we investigated if metabolic activities act as a global modulator for the segmentation clock, finding that they are rather selective modulators. While several metabolic inhibitions extended the clock period, their effects on the key processes varied. Inhibition of glycolysis decelerated the protein degradation of Hes7 and extended the production delay but did not influence the intron delay. Electron transport chain inhibition extended Hes7 intron delay without influencing the other two processes. Combinations of distinct metabolic inhibitions exhibited synergistic effects. By contrast, temperature changes affected the clock period and all three key processes simultaneously. These results highlight the selective effects of metabolic activities on segmentation clock processes, hinting that their scaled kinetics across species may be achieved through combinations of multiple modulators.
A chemically defined oviposition attractant and repellent of Black Soldier Flies (Hermetia illucens)
Authors: Thomas Nyasha KT , Karpati Zsolt , Schmitt Thomas , Riabinina Olena 
Published: June 2024

AbstractBlack Soldier Flies (BSF),Hermetia illucens, are industrially important species. They can consume large amounts of spoilt organic material as larvae and bio-convert it to more useful biomass. Female BSF lay eggs in crevices adjacent to spoilt organic materials that serve as an oviposition attractant. These kairomones are central to maximising rearing efforts, yet the composition and origin of oviposition cues remain undefined, and no synthetic oviposition attractants are currently available. This work aimed to identify key components of naturally occurring oviposition attractants and to formulate an effective synthetic alternative for BSF. We have developed a novel oviposition assay and found larval food- and frass-based attractants to be the most effective at centralizing egg laying. We have identified the volatile compounds in the headspaces of putative attractants and established that the antennae of the female flies respond to some of these compounds. Behavioural validation using synthetic compounds allowed us to generate a mixture of 5 compounds (p-cresol, decanal, sulcatone, pentanoic acid, acetophenone) that cues oviposition as efficiently as currently used natural oviposition attractants. We also identified a synthetic mixture that deters oviposition in BSF. The synthetic attractant and repellent we generated are likely to simplify BSF rearing in research and industrial settings.
Models trained to predict differential expression across plant organs identify distal and proximal regulatory regions
Authors: Tross Michael C. , Duggan Gavin , Shrestha Nikee , Schnable James C. 
Published: June 2024

AbstractA large proportion of standing phenotypic variation is explained by genetic variation in noncoding regulatory regions. However, tools for the automated identification and characterization of noncoding regulatory sequences in genomes have lagged far behind those employed to annotate and predict the functions of protein coding sequences. We developed a modified transformer model and trained it to predict relative patterns of expression across a diverse set of tissues given a large sequence window for each gene of interest in the maize (Zea mays) genome. Nucleotides in the input DNA sequence with high saliency in gene expression pattern prediction overlapped with regions identified via comparative genomic or chromatin-based approaches as potential regulatory sequences. High saliency regions identified in a second species, sorghum (Sorghum bicolor), without species-specific training were also associated with potential regulatory sequences in noncoding regions upstream and downstream of each gene of interest. The potential impact of a scaleable and transferable approach to identifying regulatory sequences using saliency calculated from large context window models spans multiple applications. Specific use cases could include genome annotation, interpretation of natural genetic variation, and targeted editing in noncoding regions to alter patterns of levels of gene expression.
The disease-causing tau V337M mutation induces tau hypophosphorylation and perturbs axon morphology pathways
Authors: Mohl Gregory A. , Dixon Gary , Marzette Emily , McKetney Justin , Samelson Avi J. , Pereda Serras Carlota , Jin Julianne , Li Andrew , Boggess Steven C. , Swaney Danielle L. , Kampmann Martin 
Published: June 2024

AbstractTau aggregation is a hallmark of several neurodegenerative diseases, including Alzheimer’s disease and frontotemporal dementia. There are disease-causing variants of the tau-encoding gene,MAPT, and the presence of tau aggregates is highly correlated with disease progression. However, the molecular mechanisms linking pathological tau to neuronal dysfunction are not well understood due to our incomplete understanding of the normal functions of tau in development and aging and how these processes change in the context of causal disease variants of tau. To address these questions in an unbiased manner, we conducted multi-omic characterization of iPSC-derived neurons harboring theMAPTV337M mutation. RNA-seq and phosphoproteomics revealed that both V337M tau and tau knockdown consistently perturbed levels of transcripts and phosphorylation of proteins related to axonogenesis or axon morphology. Surprisingly, we found that neurons with V337M tau had much lower tau phosphorylation than neurons with WT tau. We conducted functional genomics screens to uncover regulators of tau phosphorylation in neurons and found that factors involved in axonogenesis modified tau phosphorylation in bothMAPTWT andMAPTV337M neurons. Intriguingly, the p38 MAPK pathway specifically modified tau phosphorylation inMAPTV337M neurons. We propose that V337M tau might perturb axon morphology pathways and tau hypophosphorylation via a “loss of function” mechanism, which could contribute to previously reported cognitive changes in preclinicalMAPTgene carriers.
DNA barcode developement based on chloroplast and ITS genes for species identification of endangered and threated species of Western Ghats, India
Authors: Fatima Tanzeem , Srividya MN , Singh Raj Kishore 
Published: June 2024

AbstractAccurate identification is crucial for conserving species, especially in regions such as the Western Ghats, where trade poses a significant threat to endangered and threatened forest species. Traditional morphology-based identification can be challenging and time-consuming, leading to inaccuracies, especially with similar-looking species or dried specimens. Therefore, DNA barcoding offers a potent solution for precise species identification to address illicit trade and address impactful conservation measures. DNA barcoding is a taxonomic technique that uses standardized short DNA sequences to differentiate and classify species. This approach is especially valuable when morphological characteristics alone are insufficient for accurate species identification. In this study, we focused on the development of a DNA barcoding system for the efficient and accurate identification of threatened and endangered important forest species of Western Ghats Karnataka. To develop the DNA barcoding system, a multilocus approach utilizing sixteen standard DNA barcoding markers was used. A total of 47 threatened and endangered forest species from the Western Ghats were selected for this study. Using a larger number of markers to develop DNA barcodes led to the most precise species identification rates. Moreover, the wide availability of DNA barcode databases allows for quick and accurate species identification. In our study, we observed the highest amplification rates for rbcL1 (40 species), psbtrnH2 (36 species), and PsbA-trnH1 (33 species). DNA amplification varied from 11.76% to 94.11%. Notably, the highest DNA amplification rates were detected forA. wightii(94.11%) andA. hondala (92.34%), both of which belong to the Arecaceae and Passifloraceae families, respectively. Sequencing success rates ranged from 37.5% to 100%. This study will aid in the development of a database of available threatened forest species in western Ghats Karnataka and other regions.
DIP2BCGG repeat expansion in siblings with neurodevelopmental disability and progressive movement disorder
Authors: Théberge Emilie T. , Durbano Kate , Demailly Diane , Huby Sophie , Mohajeri Arezoo ,   Care4Rare Canada Consortium, van Karnebeek Clara , Horvath Gabriella A. , Usdin Karen , Lehman Anna , Cif Laura , Richmond Phillip A. 
Published: June 2024

AbstractBackgroundTrinucleotide repeat expansions are an emerging class of genetic variants associated with several movement disorders. Unbiased genome-wide analyses can reveal novel genotype-phenotype associations and provide a diagnosis for patients and families.ObjectivesTo identify the genetic cause of a severe progressive movement disorder phenotype in two affected brothers.MethodsA family of two affected brothers and unaffected parents had extensive phenotyping and natural history followed since birth. Whole-genome and long-read sequencing methods were used to characterize genetic variants and methylation status. Results: We describe a CGG repeat expansion in the 5’-untranslated region ofDIP2Bin two affected male siblings presenting with a novelDIP2Bphenotype including neurodevelopmental disability, dysmorphic traits, and a severe progressive movement disorder (prominent chorea, dystonia, and ataxia).ConclusionsThis is the first report of a severe progressive movement disorder phenotype attributed to a CGG repeat expansion in theDIP2B5’-UTR.