bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brain implantation of tissue-level-soft bioelectronics via embryonic development
Authors: Sheng Hao , Liu Ren , Li Qiang , Lin Zuwan , He Yichun , Blum Thomas S. , Zhao Hao , Tang Xin , Wang Wenbo , Jin Lishuai , Wang Zheliang , Hsiao Emma , Le Floch Paul , Shen Hao , Lee Ariel J. , Jonas-Closs Rachael Alice , Briggs James , Liu Siyi , Solomon Daniel , Wang Xiao , Lu Nanshu , Liu Jia 
Published: June 2024

AbstractThe design of bioelectronics capable of stably tracking brain-wide, single-cell, and millisecond-resolved neural activities in the developing brain is critical to the study of neuroscience and neurodevelopmental disorders. During development, the three-dimensional (3D) structure of the vertebrate brain arises from a 2D neural plate1,2. These large morphological changes previously posed a challenge for implantable bioelectronics to track neural activity throughout brain development3–9. Here, we present a tissue-level-soft, sub-micrometer-thick, stretchable mesh microelectrode array capable of integrating into the embryonic neural plate of vertebrates by leveraging the 2D-to-3D reconfiguration process of the tissue itself. Driven by the expansion and folding processes of organogenesis, the stretchable mesh electrode array deforms, stretches, and distributes throughout the entire brain, fully integrating into the 3D tissue structure. Immunostaining, gene expression analysis, and behavioral testing show no discernible impact on brain development or function. The embedded electrode array enables long-term, stable, brain-wide, single-unit-single-spike-resolved electrical mapping throughout brain development, illustrating how neural electrical activities and population dynamics emerge and evolve during brain development.
Electromigration of Charged Analytes Through Immiscible Fluids in Multiphasic Electrophoresis
Authors: Islam Md Nazibul , Liu Yang , Herr Amy E 
Published: June 2024

ABSTRACTMultiphasic buffer systems have been of greatest interest in electrophoresis and liquid-liquid electrotransfer; this study extends that foundation by exploring the interplay of the geometric and viscous properties of an interleaving oil layer on the electrotransfer of a charged analyte from an aqueous solution into a hydrogel. We utilized finite element analysis to examine two complementary configurations: one being electrotransfer of a charged analyte (protein) in an aqueous phase into a surrounding hydrogel layer and another being electrotransfer of the protein from that originating aqueous phase – through an interleaving oil layer of predetermined viscosity and thickness – and into a surrounding hydrogel layer. Results indicate that the presence of an oil layer leads to increased skew of the injected peak. To explain this difference in injection dispersion, we utilize Probstein’s framework and compare the Péclet (Pe) number with the ratio between length scales characteristic to the axial and radial dispersion, respectively. The formulation assigns electrotransfer conditions into six different dispersion regimes. We show that the presence or absence of an interleaving oil layer moves the observed peak dispersion into distinct electrotransfer regimes; the presence of an oil layer augments the electrophoretic mobility mismatch between the different phases, resulting in a five-fold increase in Pe and a six-fold increase in the ratio between the axial to radial dispersion characteristic lengths. We further show that oil viscosity significantly influences resultant injection dispersion. A decrease in oil-layer viscosity from 0.08 Pa·s to 0.02 Pa·s results in a >100% decrease in injection dispersion. Our theoretical predictions were experimentally validated by comparing the electrotransfer regimes of three different mineral oil samples. We show that lowering the oil viscosity to 0.0039 Pa·s results in an injection regime similar to that of the absence of an oil layer. Additionally, we measure the migration distance and show that average electromigration velocity over the transit duration is inversely proportional to the viscosity of an interleaving oil layer. Understanding of the impact of electrotransfer of charged species across multiple immiscible fluid layers on peak dispersion informs the design of multiphasic electrophoresis systems.
The association between street construction projects and community violence in New York City
Authors: Bushover Brady , Kim Andrew , Mehranbod Christina A. , Roberts Leah E. , Gobaud Ariana N. , Eschliman Evan L. , Fish Carolyn , Gao Xiang , Zadey Siddhesh , Morrison Christopher N. 
Published: June 2024

AbstractIntroductionCommunity violence is a major cause of injury and death in the United States. Empirical studies have identified that some place-based interventions of urban private places, such as remediations of vacant lots and buildings, are associated with reductions in community violence in surrounding areas. The aim of this study was to examine whether routine maintenance and repair of urban public places (e.g., street construction projects) are also associated with reductions in community violence, proxied by violent crime.MethodThis staggered adoption difference-in-difference analysis investigated the association between street construction projects and community violence in New York City from 2010-2019, divided into 40 calendar quarters. The units of analysis were street-quarters (n = 155,280). Intervention street-quarters were those with completed projects in 2010-2019; control streets were those where projects were scheduled but not completed before 2019. The outcome of community violence was proxied by counts of crime and violence incidents reported to the New York Police Department, within street-quarters.ResultsThere were 79,592 street-quarters with any community violence incidents (51.2%). We found that street construction projects were associated with a decrease in reckless endangerment (ATT = -0.013; 95% CI = -0.021, -0.004), robbery (ATT = -0.035; 95% CI = -0.063, -0.007), and weapons offenses (ATT = -0.016; 95% CI = -0.031, -0.001) occurring on street-quarters.ConclusionStreet construction projects may be yet another type of place-based intervention to reduce community violence.
The Interplay of Prior Information and Motion Cues in Resolving Visual Ambiguity in Agent Perception
Authors: Er Sena , Elmas Hüseyin O. , Urgen Burcu A. 
Published: June 2024

AbstractAgent perception is essential for social interaction, allowing individuals to interpret and respond to the actions of others within dynamic environments. In this study, we examined on how prior knowledge and motion cues are integrated to influence the temporal dynamics of perceiving agents. In order to make realistic but ambiguous stimuli in motion and form characteristics, we used human, robot, and android agents. Using temporal representational similarity analysis (RSA) on EEG recordings, we analyzed the representation of agent identities under varying conditions—Still versus Moving stimuli and Prior versus Naive contexts. Our findings revealed that prior knowledge and motion cues interact to produce distinct temporal patterns of representation. In the naive condition, information about the agent persisted longer during still presentations than during moving ones, suggesting that the processing of agents depends on the availability of motion information and prior information. Moreover, motion information affects the temporal processing of agents when no prior information about agents is available. These results highlight the critical roles of both bottom-up sensory inputs and top-down expectations and their interactions in resolving the ambiguities inherent in agent perception.
ProtEx: A Retrieval-Augmented Approach for Protein Function Prediction
Authors: Shaw Peter , Gurram Bhaskar , Belanger David , Gane Andreea , Bileschi Maxwell L. , Colwell Lucy J. , Toutanova Kristina , Parikh Ankur P. 
Published: June 2024

AbstractMapping a protein sequence to its underlying biological function is a critical problem of increasing importance in biology. In this work, we propose ProtEx, a retrieval-augmented approach for protein function prediction that leverages exemplars from a database to improve accuracy and robustness and enable generalization to unseen classes. Our approach relies on a novel multi-sequence pretraining task, and a fine-tuning strategy that effectively conditions predictions on retrieved exemplars. Our method achieves state-of-the-art results across multiple datasets and settings for predicting Enzyme Commission (EC) numbers, Gene Ontology (GO) terms, and Pfam families. Our ablations and analysis highlight the impact of conditioning predictions on exemplar sequences, especially for classes and sequences less well represented in the training data.
A diverse and distinct microbiome inside living trees
Authors: Arnold Wyatt , Gewirtzman Jonathan , Raymond Peter A. , Duguid Marlyse , Brodersen Craig , Brown Cade , Norbraten Naomi , Wood Qespi T’ika Vizcarra , Bradford Mark A. , Peccia Jordan 
Published: June 2024

AbstractDespite significant advances in microbiome research across various environments1, the microbiome of Earth’s largest biomass reservoir– the wood of living trees2– remains largely unexplored. This oversight neglects a critical aspect of global biodiversity and potentially key players in tree health and forest ecosystem functions. Here we illuminate the microbiome inhabiting and adapted to wood, and further specialized to individual host species. We demonstrate that a single tree can host approximately a trillion microbes in its aboveground internal tissues, with microbial communities partitioned between heartwood and sapwood, each maintaining a distinct microbiome with minimal similarity to other plant tissues or nearby ecosystem components. Notably, the heartwood microbiome emerges as a unique ecological niche, distinguished in part by endemic archaea and anaerobic bacteria that drive consequential biogeochemical processes. Our research supports the emerging idea of a plant as a “holobiont”3,4—a single ecological unit comprising host and associated microorganisms—and parallels human microbiome research in its implications for host health, disease, and functionality5. By mapping the structure, composition, and potential sources and functions of the tree internal microbiome, our findings pave the way for novel insights into tree physiology and forest ecology, and establish a new frontier in environmental microbiology.
Dimensionality Reduction and Denoising of Spatial Transcriptomics Data Using Dual-Channel Masked Graph Autoencoder
Authors: Min Wenwen , Fang Donghai , Chen Jinyu , Zhang Shihua 
Published: June 2024

AbstractRecent advances in spatial transcriptomics (ST) technology allow researchers to comprehensively measure gene expression patterns at the level of individual cells or even subcellular compartments while preserving the spatial context of their tissue. Spatial domain identification is a critical task in analyzing the ST data. However, effectively capturing distinctive gene expression features and relationships between genes poses a significant challenge. We develop a graph self-supervised learning method STMask for the analysis and exploration of the ST data. STMask combines the masking mechanism with a graph autoencoder, compelling the gene representation learning channel to acquire more expressive representations. Simultaneously, it combines the masking mechanism with graph self-supervised contrastive learning methods, pulling together the embedding distances between spatially adjacent points and pushing apart the representations of different clusters, allowing the gene relationship learning channel to learn more comprehensive relationships. The applications of STMask to four ST datasets demonstrate that STMask outperforms state-of-the-art methods in various tasks, including spatial clustering and trajectory inference. Source code is available athttps://github.com/donghaifang/STMask.Author summarySpatial Transcriptomics (ST) is an emerging transcriptomic sequencing technology aimed at revealing the spatial distribution of gene expression and cell types within tissues. This method enables the acquisition of gene expression profiles at the level of individual cells or spots within the tissue, uncovering the spatial expression patterns of genes. However, accurately identifying spatial domains in ST data remains challenging. In our study, we introduce STMask, a self-supervised learning method that combines a dual-channel masked graph autoencoder with masking and contrastive learning. Our work contributes primarily in two aspects: (1) We propose a novel graph self-supervised learning method (STMask) specifically tailored for the analysis and research of ST data, which enhances the ability to capture the unique features of gene expression and spatial relationships within tissues. (2) Through comprehensive experiments, STMask provides valuable insights into biological processes, particularly in the context of breast cancer. It identifies enrichment of various differentially expressed genes in tumor regions, such asIGHG1, which can serve as effective targets for cancer therapy.
Improving Olfactory Receptor Structure Modeling via Hybrid Methods
Authors: Berwal Bhavika , Saha Pinaki , Kumar Ritesh 
Published: June 2024

AbstractUnderstanding the structure of Olfactory Receptors (ORs) is pivotal in deciphering the molecular complexities of smell, a sense crucial for health, and survival, and holding immense therapeutic potential. However, the scarcity of detailed experimental data on ORs has hindered progress, demanding inventive approaches.This study explores various structure prediction methods tailored to ORs based on their phylogenetic and structural characteristics, using OR51E2 as a reference. We employed a hybrid homology modeling approach, utilizing AlphaFold structures, yielding models with lower RMSD (1.019°A across pruned/significant pairs and 2.33°A over-all) and enhanced structural metrics compared to standalone AlphaFold (RMSD - 2.5°A) predictions. Our pipeline successfully replicated experimental findings for OR51E2 and was applied to homologous ORs: OR51E1, OR51D1, and OR51G2. Various tools were also used to predict potential binding sites for each receptor. Molecular dynamics simulations validated the stability of these OR models in a lipid bilayer environment, with biophysical analyses revealing that AlphaFold models exhibit relatively less ideal behavior compared to the Hybrid Model. Our study presents a targeted approach to investigate and generate optimum OR structures for further conformational analyses.
b-move: faster bidirectional character extensions in a run-length compressed index
Authors: Depuydt Lore , Renders Luca , Van de Vyver Simon , Veys Lennart , Gagie Travis , Fostier Jan 
Published: June 2024

AbstractDue to the increasing availability of high-quality genome sequences, pan-genomes are gradually replacing single consensus reference genomes in many bioinformatics pipelines to better capture genetic diversity. Traditional bioinformatics tools using the FM-index face memory limitations with such large genome collections. Recent advancements in run-length compressed indices like Gagie et al.’s r-index and Nishimoto and Tabei’s move structure, alleviate memory constraints but focus primarily on backward search for MEM-finding. Arakawa et al.’s br-index initiates complete approximate pattern matching using bidirectional search in run-length compressed space, but with significant computational overhead due to complex memory access patterns. We introduce b-move, a novel bidirectional extension of the move structure, enabling fast, cache-efficient bidirectional character extensions in run-length compressed space. It achieves bidirectional character extensions up to 8 times faster than the br-index, closing the performance gap with FM-index-based alternatives, while maintaining the br-index’s favorable memory characteristics. For example, all available completeE. coligenomes on NCBI’s RefSeq collection can be compiled into a b-move index that fits into the RAM of a typical laptop. Thus, b-move proves practical and scalable for pan-genome indexing and querying. We provide a C++ implementation of b-move, supporting efficient lossless approximate pattern matching including locate functionality, available athttps://github.com/biointec/b-moveunder the AGPL-3.0 license.FundingLore Depuydt: PhD Fellowship FR (1117322N), Research Foundation – Flanders (FWO)Luca Renders: PhD Fellowship SB (1SE7822N), Research Foundation – Flanders (FWO)Travis Gagie: NSERC Discovery Grant RGPIN-07185-2020 to Travis Gagie and NIH grant R01HG011392 to Ben Langmead
Cycling Cadence Selections at Different Saddle Heights Minimize Muscle Activation Rather Than Energy Cost
Authors: Riveros-Matthey Cristian D. , Connick Mark J. , Lichtwark Glen A. , Carroll Timothy J. 
Published: June 2024

AbstractUnlike walking and running, people do not consistently choose cadences that minimize energy consumption when cycling. Assuming a common objective function for all forms of locomotion, this suggests either that the neural control system relies on indirect sensorimotor cues to energetic cost that are approximately accurate during walking but not cycling, or that an alternative objective function applies that correlates with energy expenditure in walking but not cycling. This study compared how objective functions derived as proxies to 1) energy cost or 2) an avoidance of muscle fatigue predicted self-selected cycling cadences (SSC) at different saddle heights. Saddle height systematically affected SSC, with lower saddles increasing SSC and higher saddles decreasing SSC. Both fatigue-avoidance and energy-expenditure cost functions derived from muscle activation measurements showed minima that closely approximated the SSCs. By contrast, metabolic power derived fromVO2uptake was minimal at cadences well below the SSC across all saddle height variations. The mismatch between the cadence versus muscle activation and the cadence versus metabolic energy relations is likely due to additional energy costs associated with performing mechanical work at higher cadences. The results suggest that the nervous system places greater emphasis on muscle activation than on energy consumption for action selections in cycling.
Bacterial growth dynamics on a surface having a particulate antimicrobial agent
Authors: Talebpour Cyrus , Fani Fereshteh , Salimnia Hossein , Ouellette Marc , Alamdari Houshang 
Published: June 2024

AbstractThe morphological dynamics of microbial cell proliferation on an antimicrobial surface at an early growth stage was studied withEscherichia colion the surface of a gel supplied with nanostructured AgNbO3antimicrobial particles. We demonstrated an inhibitory surface concentration, analogous to minimum inhibitory concentration, beyond which the growth of colonies and formation of biofilm are inhibited. In contrast, at lower concentrations, colonies circumvent the antimicrobial activity of the particles and grow with a short lag time of a few hours. The applicability of these findings, in terms of estimating inhibitory surface concentration, was tested in the case of antimicrobial polymethyl methacrylate (PMMA) bone cement.
Lysophosphatidylcholine acyltransferase 1 suppresses nanoclustering and function of KRAS
Authors: Arora Neha , Liang Hong , Yao Wantong , Ying Haoqiang , Liu Junchen , Zhou Yong 
Published: June 2024

AbstractKRAS is frequently mutated in cancer, contributing to 20% of all human cancer especially pancreatic, colorectal and lung cancer. Signaling of the constitutively active KRAS oncogenic mutants is mostly compartmentalized to proteolipid nanoclusters on the plasma membrane (PM). Signaling nanoclusters of many KRAS mutants selectively enrich phosphatidylserine (PS) lipids with unsaturatedsn-2acyl chains, but not the fully saturated PS species. Thus, remodeling PS acyl chains may suppress KRAS oncogenesis. Lysophosphatidylcholine acyltransferases (LPCATs) remodelsn-2acyl chains of phospholipids, with LPCAT1 preferentially generating the fully saturated lipids. Here, we show that stable expression of LPCAT1 depletes major PS species with unsaturated sn-2 chains while decreasing minor phosphatidylcholine (PC) species with the corresponding acyl chains. LPCAT1 expression more effectively disrupts the nanoclustering of oncogenic GFP-KRASG12V, which is restored by acute addback of exogenous unsaturated PS. LPCAT1 expression compromises signaling and oncogenic activities of the KRAS-dependent pancreatic tumor lines. LPCAT1 expression sensitizes human pancreatic tumor MiaPaCa-2 cells to KRASG12Cspecific inhibitor, Sotorasib. Statistical analyses of patient data further reveal that pancreatic cancer patients with KRAS mutations express less LPCAT1. Higher LPCAT1 expression also improves survival probability of pancreatic and lung adenocarcinoma patients with KRAS mutations. Thus, PS acyl chain remodeling selectively suppresses KRAS oncogenesis.
Lipid loss and compositional change during preparation of liposomes by common biophysical methods
Authors: Kim Eunice , Graceffa Olivia , Broweleit Rachel , Ladha Ali , Boies Andrew , Rawle Robert J. 
Published: June 2024

AbstractLiposomes are widely used as model lipid membrane platforms in many fields, ranging from basic biophysical studies to drug delivery and biotechnology applications. Various methods exist to prepare liposomes, but common procedures include thin-film hydration followed by extrusion, freeze-thaw, and/or sonication. These procedures have the potential to produce liposomes at specific concentrations and membrane compositions, and researchers often assume that the concentration and composition of their liposomes are similar to, if not identical, to what would be expected if no lipid loss occurred during preparation. However, lipid loss and concomitant biasing of lipid composition can in principle occur at any preparation step due to nonideal mixing, lipid-surface interactions, etc. Here, we report a straightforward method using HPLC-ELSD to quantify the lipid concentration and membrane composition of liposomes, and apply that method to study the preparation of simple POPC/cholesterol liposomes. We examine many common steps in liposome formation, including vortexing during re-suspension, hydration of the lipid film, extrusion, freeze-thaw, sonication, and the percentage of cholesterol in the starting mixture. We found that the resuspension step can play an outsized role in determining the overall lipid loss (up to ∼50% under seemingly rigorous procedures). The extrusion step yielded smaller lipid losses (∼10-20%). Freeze-thaw and sonication could both be employed to improve lipid yields. Hydration times up to 60 minutes and increasing cholesterol concentrations up to 50 mole% had little influence on lipid recovery. Fortunately, even conditions with large lipid loss did not substantially influence the target membrane composition more than ∼5% under the conditions we tested. From our results, we identify best practices for producing maximum levels of lipid recovery and minimal changes to lipid composition during liposome preparation protocols. We expect our results can be leveraged for improved preparation of model membranes by researchers in many fields.Statement of SignificanceLiposomes are spherical lipid membranes that can be prepared by a variety of biophysical techniques. Researchers use liposomes in a variety of ways, including fundamental biophysical studies of lipid membranes, in drug delivery, drug formulation, and other biotechnology applications. In this report, we study the process to prepare liposomes by several common techniques and validate how reliable each technique is at producing consistent liposome concentrations and lipid compositions. We identify best practices for researchers to produce reliable liposome preparations.