bluuebunny/crossref_metadata_2025_split huggingface dataset:
Directed Shortest Walk on Temporal Graphs
Authors: Khodaverdian Alex , Yosef Nir 
Published: July 2022

AbstractBackgroundThe use of graphs as a way of abstracting and representing biological systems has provided a powerful analysis paradigm. Specifically, graph optimization algorithms are routinely used to address various connectivity queries, such as finding paths between proteins in a protein-protein interaction network, while maximizing objectives such as parsimony. While present studies in this field mostly concern static graphs, new types of data now motivate the need to account for changes that might occur to the elements (nodes) that are represented by the graph on the relationships (edges) between them.Results and DiscussionWe define the notion of Directed Temporal Graphs as a series of directed subgraphs of an underlying graph, ordered by time, where only a subset of vertices and edges are present. We then build up towards the Time Conditioned Shortest Walk problem on Directed Temporal Graphs: given a series of time ordered directed graphs, find the shortest walk from any given source node at time point 1 to a target node at time T ≥ 1, such that the walk is consistent (monotonically increasing) with the timing of nodes and edges. We show, contrary to the Directed Shortest Walk problem which can be solved in polynomial time, that the Time Conditioned Shortest Walk (TCSW) problem is NP-Hard, and is hard to approximate to factor for T ≥ 3 and ε > 0. Lastly, we develop an integer linear program to solve a generalized version of TCSW, and demonstrate its ability to reach optimality with instances of the human protein interaction network.ConclusionWe demonstrate that when extending the shortest walk problem in computational biology to account for multiple ordered conditions, the problem not only becomes hard to solve, but hard to approximate, a limitation which we address via a new solver. From this narrow definition of TCSW, we relax the constraint of time consistency within the shortest walk, deriving a direct relationship between hardness of approximation and the allowable step size in our walk between time conditioned networks. Lastly we briefly explore a variety of alternative formulations for this problem, providing insight into both tractable and intractable variants.AvailabilityOur solver for the general k-Time Condition Shortest Walk problem is available at https://github.com/YosefLab/temporal_condition_shortest_walk
Integration of microprism and microelectrode arrays enables simultaneous electrophysiology and two-photon imaging across all cortical layers
Authors: Yang Qianru , Wu Bingchen , Castagnola Elisa , Pwint May Yoon , Williams Nathaniel , Vazquez Alberto L. , Cui X. Tracy 
Published: July 2022

AbstractElectrophysiology is a vital tool in neuroscience research with increasing translational value. It is used to record or modulate neuronal activity with high temporal but lower spatial resolution. Optical technologies, such as two-photon microscopy (TPM) can complement electrophysiological recordings with large-scale imaging at cellular resolution. Combining these two provides a powerful platform to elucidate and coordinate multimodal functions. Prior attempts have been limited to the superficial brain from a top-down optical view. Here, we describe a novel combination of transparent microelectrode arrays (MEAs) with glass microprisms for simultaneous electrophysiology and optical imaging of all cortical layers in a vertical plane. We tested our device in Thy1-GCaMP6 mice for over 4 months and demonstrated its capability for multisite single-unit recording, microstimulation, and simultaneous TPM calcium imaging. Using this setup, we reveal how amplitude, frequency, and depth of microstimulation impact neural activation patterns across the cortical column. This work presents a multimodal tool that extends integrated electrophysiology and optical imaging from the superficial brain to the whole cortical column, opening new avenues of neuroscience research and neurotechnology development.
Innate Immune Stimulation using 3D Wireframe DNA Origami
Authors: Du Rebecca R. , Cedrone Edward , Dobrovolskaia Marina A. , Bathe Mark 
Published: July 2022

ABSTRACT3D wireframe DNA origami have programmable structural and sequence features that render them potentially suitable for prophylactic and therapeutic applications. However, their innate immunological properties, which stem from parameters including geometric shape and CpG content, remain largely unknown. Here, we investigate the immunostimulatory properties of 3D wireframe DNA origami on the TLR9 pathway using both reporter cell lines and primary immune cells. Our results suggest that bare 3D polyhedral wireframe DNA origami induce minimal TLR9 activation despite the presence of numerous internal CpG dinucleotides. However, when displaying multivalent CpG-containing ssDNA oligos, wireframe DNA origami induce robust TLR9 pathway activation, along with enhancement of downstream immune response as evidenced by increases in Type I and Type III IFN production in peripheral blood mononuclear cells. Further, we find that CpG copy number and spatial organization each contribute to the magnitude of TLR9 signaling, and that NANP-attached CpGs do not require phosphorothioate stabilization to elicit signaling. These results suggest key design parameters for wireframe DNA origami that can be programmed to modulate immune pathway activation controllably for prophylactic and therapeutic applications.
BayesTME: A unified statistical framework for spatial transcriptomics
Authors: Zhang Haoran , Hunter Miranda V. , Chou Jacqueline , Quinn Jeffrey F. , Zhou Mingyuan , White Richard , Tansey Wesley 
Published: July 2022

AbstractSpatial variation in cellular phenotypes underlies heterogeneity in immune recognition and response to therapy in cancer and many other diseases. Spatial transcriptomics (ST) holds the potential to quantify such variation, but existing analysis methods address only a small part of the analysis challenge, such as spot deconvolution or spatial differential expression. We present BayesTME, an end-to-end Bayesian method for analyzing spatial transcriptomics data. BayesTME unifies several previously distinct analysis goals under a single, holistic generative model. This unified approach enables BayesTME to (i) be entirely reference-free without any need for paired scRNA-seq, (ii) outperform a large suite of methods in quantitative benchmarks, and (iii) uncover a new type of ST signal: spatial differential expression within individual cell types. To achieve the latter, BayesTME models each phenotype as spatially adaptive and discovers statistically significant spatial patterns amongst coordinated subsets of genes within phenotypes, which we term spatial transcriptional programs. On human and zebrafish melanoma tissues, BayesTME identifies spatial transcriptional programs that capture fundamental biological phenomena like bilateral symmetry, differential expression between interior and surface tumor cells, and tumor-associated fibroblast and macrophage reprogramming. Our results demonstrate BayesTME’s power in unlocking a new level of insight from spatial transcriptomics data and fostering a deeper understanding of the spatial architecture of the tumor microenvironment. BayesTME is open source and publicly available (https://github.com/tansey-lab/bayestme).
Unifying the Identification of Biomedical Entities with the Bioregistry
Authors: Hoyt Charles Tapley , Balk Meghan , Callahan Tiffany J. , Domingo-Fernández Daniel , Haendel Melissa A. , Hegde Harshad B. , Himmelstein Daniel S. , Karis Klas , Kunze John , Lubiana Tiago , Matentzoglu Nicolas , McMurry Julie , Moxon Sierra , Mungall Christopher J. , Rutz Adriano , Unni Deepak R. , Willighagen Egon , Winston Donald , Gyori Benjamin M. 
Published: July 2022

ABSTRACTThe standardized identification of biomedical entities is a cornerstone of interoperability, reuse, and data integration in the life sciences. Several registries have been developed to catalog resources maintaining identifiers for biomedical entities such as small molecules, proteins, cell lines, and clinical trials. However, existing registries have struggled to provide sufficient coverage and metadata standards that meet the evolving needs of modern life sciences researchers. Here, we introduce the Bioregistry, an integrative, open, community-driven metaregistry that synthesizes and substantially expands upon 23 existing registries. The Bioregistry addresses the need for a sustainable registry by leveraging public infrastructure and automation, and employing a progressive governance model centered around open code and open data to foster community contribution. The Bioregistry can be used to support the standardized annotation of data, models, ontologies, and scientific literature, thereby promoting their interoperability and reuse. The Bioregistry can be accessed throughhttps://bioregistry.ioand its source code and data are available under the MIT and CC0 Licenses athttps://github.com/biopragmatics/bioregistry.
Elsewhere or Blanked? Ongoing mental states are regulated by pupil-linked arousal and attentional style in healthy ageing
Authors: Koroma Matthieu , Robert de Beauchamp Aurèle , Mortaheb Sepehr , Boulakis Paradeisios Alexandros , Bastin Christine , Demertzi Athena 
Published: July 2022

AbstractSpontaneous thinking significantly relies on attention and arousal. As these cognitive faculties change with age, we aimed at providing a comprehensive account to ongoing mental states in seniors, testing how these are influenced by attentional control and arousal. Using experience sampling at rest, 20 senior (65-75yrs) and 20 young participants (20-30yrs) were prompted to report mind-wandering (MW), sensory-related thoughts (S), and the newly introduced state of mind blanking (MB). Attentional control was assessed with the Attentional Style Questionnaire, and arousal with continuous monitoring of pupil diameter. Both age groups showed equally high occurrences of MW compared to MB or S. For young responders, we replicated that MW was more prevalent in easily-distracted participants and that it associated with higher arousal. In seniors, though, MB was more prevalent in easily-distracted participants, and it was associated with higher arousal, reversing the pattern found in young adults and focused seniors. Overall, our results show that attentional control and arousal jointly regulate ongoing mental states in an age-dependent manner and uncover the presence a specific profile of ongoing mental state regulation in healthy aging, being a potentially critical marker of age-associated diseases.
Multiplexing working memory and time: encoding retrospective and prospective information in neural trajectories
Authors: Zhou Shanglin , Seay Michael , Taxidis Jiannis , Golshani Peyman , Buonomano Dean V. 
Published: July 2022

ABSTRACTWorking memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components. In both cases the task-irrelevant component influenced performance. RNN simulations revealed that cue-specific neural sequences, which multiplexed WM and time, emerged as the dominant regime that captured the behavioral findings. Over the course of training RNN dynamics transitioned from low-dimensional ramps to high-dimensional neural sequences, and depending on task requirements, steady-state or ramping activity was also observed. Analysis of RNN structure revealed that neural sequences relied primarily on inhibitory connections, and could survive the deletion of all excitatory-to- excitatory connections. Our results suggest that in some instances WM is encoded in time-varying neural activity because of the importance of predicting when WM will be used.
Evaluating the Reliability of AlphaFold 2 for Unknown Complex Structures with Deep Learning
Authors: Xiong Hao , Han Long , Wang Yue , Chai Pengxin 
Published: July 2022

AbstractRecently released AlphaFold 2 shows a high accuracy when predicting most of the well- structured single protein chains, and subsequent works have also shown that providing pseudo-multimer inputs to the single-chain AlphaFold 2 can predict complex interactions among which the accuracy of predicted complexes can be easily determined by ground truth structures. However, for unknown complex structures without homologs, how to evaluate the reliability of the predicted structures remains a major challenge. Here, we have developed AlphaFold-Eva, a deep learning-based method that learns geometry information from complex structures to evaluate AlphaFold 2. Using different types of sub-complexes of the central apparatus and recently released PDB data, we demonstrate that the reliability of unknown complex structures predicted by AlphaFold 2 is significantly affected by surface ratio, contact surface and dimension ratio. Our findings suggest that the reliability of predicted structures can be directly learned from the intrinsic structural information itself. Therefore, AlphaFold-Eva provides a promising solution to quantitatively validate the predicted structures of unknown complexes, even without a reference.
The cut site specificity of the influenza A virus endoribonuclease PA-X allows it to discriminate between host and viral mRNAs
Authors: Gaucherand Lea , Iyer Amrita , Gilabert Isabel , Rycroft Chris H. , Gaglia Marta M. 
Published: July 2022

AbstractWidespread shutoff of host gene expression through RNA degradation is an advantageous way for many viruses to block antiviral responses. However, viruses still need to maintain expression of their own genes and host genes necessary for replication. The influenza A virus host shutoff endoribonuclease PA-X solves this problem by sparing viral mRNAs and some host RNAs. To understand how PA-X distinguishes between RNAs, we characterized PA-X cut sites transcriptome-wide. This analysis shows that PA-Xs from multiple influenza strains cleave RNAs at GCUG tetramers in hairpin loops. Importantly, GCUG tetramers are enriched in the human but not the influenza transcriptome. Moreover, optimal PA-X cut sites inserted in the influenza A virus genome are quickly selected against during viral replication. This finding suggests that PA-X evolved these cleavage characteristics to target host but not viral mRNAs, in a manner reminiscent of cellular self vs. non-self discrimination.
DLL3 REGULATES NOTCH SIGNALING IN SCLC
Authors: Kim Jun W. , Ko Julie H. , Sage Julien 
Published: July 2022

ABSTRACTTumor heterogeneity plays a critical role in tumor development and response to treatment. In small-cell lung cancer (SCLC), intratumoral heterogeneity is driven in part by the Notch signaling pathway, which reprograms neuroendocrine cancer cells to a less/non-neuroendocrine state. Here we investigated the atypical Notch ligand DLL3 as a biomarker of the neuroendocrine state and a regulator of cell-cell interactions in SCLC. We first built a mathematical model to predict the impact of DLL3 expression on SCLC cell populations. We next tested this model using a single-chain variable fragment (scFv) to track DLL3 expression in vivo and a new mouse model of SCLC with inducible expression of DLL3 in SCLC tumors. We found that high levels of DLL3 promote the expansion of a SCLC cell population with lower expression levels of both neuroendocrine and non-neuroendocrine markers. This work may influence how DLL3-targeting therapies are used in SCLC patients.
Mapping fetal myeloid differentiation in airway samples from premature neonates with single-cell profiling
Authors: Welfley Holly , Kylat Ranjit , Zaghloul Nahla , Halonen Marilyn , Martinez Fernando D. , Ahmed Mohamed , Cusanovich Darren A. 
Published: July 2022

AbstractSingle-cell genomic technologies hold great potential to advance our understanding of development and disease. A major limitation lies in isolating intact cells from primary tissues for profiling. Sampling methods compatible with current clinical interventions could enable longitudinal studies, the enrollment of large cohorts, and even the development of novel diagnostics. To explore single-cell RNA-seq (scRNA-seq) profiling of the cell types present at birth in the airway lumen of extremely premature (<28 weeks gestation) neonates, we isolated cells from endotracheal aspirates collected from intubated neonates within the first hour after birth. We generated data on 10 subjects, providing a rich view of airway luminal biology at a critical developmental period. Our results show that cells present in the airways of premature neonates primarily represent a continuum of myeloid differentiation, including fetal monocytes (25% of all cells), intermediate myeloid populations (48% of cells), and macrophages (2.6% of cells). To our knowledge, this is the first single-cell transcriptomic characterization of human monocytes in the neonatal airway isolated within an hour of birth. Applying trajectory analysis to the premature neonate myeloid populations, we identified two trajectories consistent with the developmental stages of interstitial and alveolar macrophages, as well as a third trajectory presenting a potential alternative pathway bridging these terminal macrophage states. While the three trajectories share many dynamic genes (5,451), they also have distinct transcriptional changes (259 alveolar-specific genes, 666 interstitial-specific genes, and 285 bridging-specific genes). Overall, our results define high quality single-cell data from cells isolated within the so-called “golden hour of birth” in extremely premature neonate airways representing complex lung biology and can be utilized in studies of human development and disease.
SIR telomere silencing depends on nuclear envelope lipids and modulates sensitivity to a lysolipid drug
Authors: Sosa Ponce Maria Laura , Remedios Mayrene Horta , Moradi-Fard Sarah , Cobb Jennifer A , Zaremberg Vanina 
Published: July 2022

AbstractThe nuclear envelope (NE) is important in maintaining genome organization. The role of lipids in the communication between the NE and telomere silencing was investigated, including how changes in lipid composition impact gene expression and overall nuclear architecture. For this purpose, yeast cells were treated with the non-metabolizable lysophosphatidylcholine analog edelfosine, known to accumulate at the perinuclear endoplasmic reticulum. Edelfosine treatment induced NE deformation and disrupted telomere clustering but not anchoring. In addition, the association of Sir4 at telomeres measured by ChIP decreased. RNA-seq analysis showed altered expression of Sir-dependent genes located at sub-telomeric (0-10 kb) regions, which was consistent with Sir4 dispersion. Transcriptomic analysis revealed that two lipid metabolic circuits were activated in response to edelfosine, one mediated by the membrane sensing transcription factors, Spt23/Mga2, and the other by a transcriptional repressor, Opi1. Activation of these combined transcriptional programs resulted in higher levels of unsaturated fatty acids and the formation of nuclear lipid droplets. Interestingly, cells lacking Sir proteins displayed resistance to unsaturated fatty acids and edelfosine, and this phenotype was connected to Rap1.GRAPHICAL ABSTRACTSummaryThe nuclear envelope (NE) is important for nuclear organization. This study shows that changes in NE lipid composition from lysolipid treatment decreases Sir4 association with telomeres, their clustering at NE, and triggers lipid-specific transcriptional circuits regulated by membrane-sensing factors.
scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single cell data
Authors: Faure Louis , Soldatov Ruslan , Kharchenko Peter V. , Adameyko Igor 
Published: July 2022

SummaryscFates provides an extensive toolset for analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a focus on cell biasing and fate splits at the level of bifurcations. It is meant to be fully integrated into scanpy ecosystem for seamless analysis of trajectories from single cell data of various modalities (e.g. RNA, ATAC).Availability and implementationscFates is released as open-source software under the BSD 3-Clause “New” License and is available from the Python Package Index at https://pypi.org/project/scFates/. The source code is available on Github at https://github.com/LouisFaure/scFates/Supplementary informationA supplementary document is provided with a complete explanation of the underlying statistics, and two figures showing examples of analysis.
A Draft Human Pangenome Reference
Authors: Liao Wen-Wei , Asri Mobin , Ebler Jana , Doerr Daniel , Haukness Marina , Hickey Glenn , Lu Shuangjia , Lucas Julian K. , Monlong Jean , Abel Haley J. , Buonaiuto Silvia , Chang Xian H. , Cheng Haoyu , Chu Justin , Colonna Vincenza , Eizenga Jordan M. , Feng Xiaowen , Fischer Christian , Fulton Robert S. , Garg Shilpa , Groza Cristian , Guarracino Andrea , Harvey William T , Heumos Simon , Howe Kerstin , Jain Miten , Lu Tsung-Yu , Markello Charles , Martin Fergal J. , Mitchell Matthew W. , Munson Katherine M. , Mwaniki Moses Njagi , Novak Adam M. , Olsen Hugh E. , Pesout Trevor , Porubsky David , Prins Pjotr , Sibbesen Jonas A. , Tomlinson Chad , Villani Flavia , Vollger Mitchell R. ,   Human Pangenome Reference Consortium, Bourque Guillaume , Chaisson Mark JP , Flicek Paul , Phillippy Adam M. , Zook Justin M. , Eichler Evan E. , Haussler David , Jarvis Erich D. , Miga Karen H. , Wang Ting , Garrison Erik , Marschall Tobias , Hall Ira , Li Heng , Paten Benedict 
Published: July 2022

AbstractThe Human Pangenome Reference Consortium (HPRC) presents a first draft human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence and are more than 99% accurate at the structural and base-pair levels. Based on alignments of the assemblies, we generated a draft pangenome that captures known variants and haplotypes, reveals novel alleles at structurally complex loci, and adds 119 million base pairs of euchromatic polymorphic sequence and 1,529 gene duplications relative to the existing reference, GRCh38. Roughly 90 million of the additional base pairs derive from structural variation. Using our draft pangenome to analyze short-read data reduces errors when discovering small variants by 34% and boosts the detected structural variants per haplotype by 104% compared to GRCh38-based workflows, and by 34% compared to using previous diversity sets of genome assemblies.