bluuebunny/crossref_metadata_2025_split huggingface dataset:
An open-source FACS automation system for high-throughput cell biology
Authors: Wiener Diane M. , Huynh Emily , Jeyakumar Ilakkiyan , Bax Sophie , Sama Samia , Cabrera Joana P. , Todorova Verina , Vangipuram Madhuri , Vaid Shivanshi , Otsuka Fumitaka , Sakai Yoshitsugu , Leonetti Manuel D. , Gómez-Sjöberg Rafael 
Published: March 2023

AbstractRecent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions (“gating”) to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument’s software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.
Label-free observation of individual solution phase molecules
Authors: Needham Lisa-Maria , Saavedra Carlos , Rasch Julia K. , Sole-Barber Daniel , Schweitzer Beau S. , Fairhall Alex J. , Vollbrecht Cecilia H. , Mehlenbacher Brandon , Zhang Zhao , Tenbrake Lukas , Pfeifer Hannes , Chapman Edwin R. , Goldsmith Randall H. 
Published: March 2023

AbstractThe vast majority of chemistry and biology occurs in solution, and new label-free analytical techniques that can help resolve solution-phase complexity at the single-molecule level can provide new microscopic perspectives of unprecedented detail. Here, we use the increased light-molecule interactions in high-finesse fiber Fabry-Pérot microcavities to detect individual biomolecules as small as 1.2 kDa with signal-to-noise ratios >100, even as the molecules are freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of sub-populations in mixed samples. Strikingly, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight can also be resolved. Detection is based on a novel molecular velocity filtering and dynamic thermal priming mechanism leveraging both photo-thermal bistability and Pound-Drever-Hall cavity locking. This technology holds broad potential for applications in life and chemical sciences and represents a major advancement in label-freein vitrosingle-molecule techniques.
Clinical Evaluation of Post-Surgical Scar Hyperesthesia; an Exploratory Longitudinal Study
Authors: Kennedy Donna L. , Hettiaratchy Shehan , Alexander Caroline M. 
Published: March 2023

AbstractEvidence for the objective clinical evaluation of scar hyperesthesia is lacking. This exploratory study investigated the clinical relevance and responsiveness of objective scar evaluation measures in adults following hand surgery.With ethical approval and consent, participants were enrolled from one NHS hospital. Patient reported and investigator completed scar morphology, cosmesis, pain and function were evaluated at 1- and 4-months post-surgery. Statistical analysis investigated the responsiveness of outcome measures and association of physical measures with the Palmar Pain Severity Scale (PPS).21 participants enrolled prior to premature study closure due to the COVID-19 pandemic; 13 completed follow up. Scar pain (p=.002); scar interference (PPI [p=.009]) and Brief Pain Inventory (BPI) scores (p=.03) improved. Neuropathic Pain Symptom Inventory (NPSI) scores demonstrated heterogeneity in scar pain; evoked pain predominated. Patient Scar Assessment Questionnaire (PSAQ) indicated improvement in cosmetic dissatisfaction and consciousness (p=.03; p=.003), respectively. Baseline psychological screening scores correlated with scar pain (p=.04), and interference (p< .001). Scar morphology, pliability and inflammation were not associated with scar pain. Significant differences in scar mechanical pain sensitivity (p=.04) and cold pain threshold (p=.05) were identified.PPS and PPI scores were responsive in a heterogeneous hand surgery sample. BPI ‘worst pain’ identified severe pain, suggesting composite scar pain scores are required. The PSAQ robustly measured scar appearance and consciousness. Psychophysical tests of mechanical and thermal sensitivity are potential candidate objective measures of scar hyperesthesia. The NPSI demonstrates clinical utility for exploring scar pain symptoms and may support the elucidation of the drivers of persistent scar pain.
Reframing dopamine: Controlling the controller at the limbic-motor interface
Authors: Lloyd Kevin , Dayan Peter 
Published: March 2023

AbstractPavlovian influences notoriously interfere with operant behaviour; various such may be associated with the release of the neuromodulator dopamine in the nucleus accumbens. One role for cognitive control is suppressing these influences. Here, using the examples of active avoidance and omission behaviour, we examine the possibility that one instrument of control is direct manipulation of the dopamine signal itself.
Gut-associated functions are favored during microbiome assembly acrossC. eleganslife
Authors: Zimmermann Johannes , Piecyk Agnes , Sieber Michael , Petersen Carola , Johnke Julia , Moitinho-Silva Lucas , Künzel Sven , Bluhm Lena , Traulsen Arne , Kaleta Christoph , Schulenburg Hinrich 
Published: March 2023

AbstractThe microbiome expresses a variety of functions that influence host biology. The range of functions depends on composition of the microbiome, which itself can change during the lifetime of the host as a consequence of neutral assembly processes, host-mediated selection, and/or environmental conditions. To date, the exact dynamics of microbiome assembly, the underlying determinants as well as the resulting effects on host-associated functions are not always well understood. Here, we used the nematodeCaenorhabditis elegansand a defined community of fully sequenced, naturally associated bacteria to study microbiome dynamics and functions across the lifetime of individual hosts under controlled experimental conditions. By applying the neutral and null models, we demonstrate that bacterial community composition initially shows strongly declining levels of stochasticity, which, however, increase during late worm life, suggesting the action of random assembly processes in aged hosts following first colonization ofC. elegans. The adult microbiome is enriched in strains of the generaOchrobactrumandEnterobacterin comparison to the direct substrate and a host-free control environment. Using pathway analysis, metabolic, and ecological modelling, we further found that the lifetime assembly dynamics lead to an increase in gut-associated functions in the host-associated microbiome, possibly indicating that the initially colonizing bacteria are beneficial for the worm. Overall, our study introduces a framework for studying microbiome assembly dynamics based on the stochastic models and inference of functions, yielding new insights into the processes determining host-associated microbiome composition and function.ImportanceThe microbiome plays a crucial role in host biology, with its functions depending on microbiome composition that can change during a host’s lifetime. To date, the dynamics of microbiome assembly and the resulting functions are not well understood. This study introduces a new approach to characterize the functional consequences of microbiome assembly by modelling both, the relevance of stochastic processes and metabolic characteristics of microbial community changes. The approach was applied to experimental time series data, obtained for the microbiome of the nematodeCaenorhabditis elegans. The results revealed significant differences in host-associated and environmental microbiomes. Stochastic processes only played a minor role, and the host showed an increase in beneficial bacteria and an enrichment of gut-associated functions, possibly indicating that the host actively shapes composition of its microbiome. Overall, this study provides a framework for studying microbiome assembly dynamics and yields new insights intoC. elegansmicrobiome functions.
Modulation of Pore Opening of Eukaryotic Sodium Channels by π-helices in S6
Authors: Choudhury Koushik , Delemotte Lucie 
Published: March 2023

AbstractVoltage-gated sodium channels are heterotetrameric sodium selective ion channels that play a central role in electrical signaling in excitable cells. With recent advances in structural biology, structures of eukaryotic sodium channels have been captured in several distinct conformations corresponding to different functional states. The secondary structure of the pore lining S6 helices of subunit DI, DII, and DIV has been captured with both short π-helix stretches and in fully α-helical conformations. The relevance of these secondary structure elements for pore gating is not yet understood. Here, we propose that a π helix in at least DI-S6, DIII-S6, and DIV-S6 results in a fully conductive state. On the other hand, the absence of π-helix in either DI-S6 or DIV-S6 yields a sub-conductance state, and its absence from both DI-S6 and DIV-S6 yields a non-conducting state. This work highlights the impact of the presence of a π-helix in the different S6 helices of an expanded pore on pore conductance, thus opening new doors towards reconstructing the entire conformational landscape along the functional cycle of Nav Channels and paving the way to the design of state-dependent modulators.Graphical Abstract
Autism is Associated within vivoChanges in Gray Matter Neurite Architecture
Authors: Christensen Zachary P. , Freedman Edward G. , Foxe John J. 
Published: March 2023

ABSTRACTPostmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) makein vivocharacterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Developmentsm(ABCD®) study 142 individuals with an Autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in Autism in the right cerebellar cortex (β=-0.005, SE =0.0015, p=0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant inpost-hocanalysis when the ASD sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in Autism and the significance of their incorporation as physiological covariates in future studies.Lay abstractChildren with autism have differences in neuron structure unique from the general populationandpopulations with attention, anxiety, and depression disorders. Brain imaging data on over 11,000 children was acquired at ages 9 and 11 years-of-age. Estimates of neuron density were derived from brain imaging data using recently validated techniques and comparative groups were composed using parent reported diagnosis of autism and other common psychiatric disorders. Consistent macro-structural changes in brain have been difficult to replicate and micro-structural changes have been historically difficult to acquire with other methodologies. We identified regional differences in the density of neuron cell bodies, neuron branching, and total neuron density in those with a reported diagnosis of ASD. Findings were consistent when compared against those with other psychiatric disorders in post-hoc analysis. These findings demonstrate the viability and importance of investigatingin vivochanges to neurons in those with autism to advance our current understanding of related physiology.
Likelihood-ratio test statistic for the finite-sample case in nonlinear ordinary differential equation models
Authors: Tönsing Christian , Steiert Bernhard , Timmer Jens , Kreutz Clemens 
Published: March 2023

AbstractLikelihood ratios are frequently utilized as basis for statistical tests, for model selection criteria and for assessing parameter and prediction uncertainties, e.g. using the profile likelihood. However, translating these likelihood ratios into p-values or confidence intervals requires the exact form of the test statistic’s distribution. The lack of knowledge about this distribution for nonlinear ordinary differential equation (ODE) models requires an approximation which assumes the so-called asymptotic setting, i.e. a sufficiently large amount of data. Since the amount of data from quantitative molecular biology is typically limited in applications, this finite-sample case regularly occurs for mechanistic models of dynamical systems, e.g. biochemical reaction networks or infectious disease models. Thus, it is unclear whether the standard approach of using statistical thresholds derived for the asymptotic large-sample setting in realistic applications results in valid conclusions. In this study, empirical likelihood ratios for parameters from 19 published nonlinear ODE benchmark models are investigated using a resampling approach for the original data designs. Their distributions are compared to the asymptotic approximation and statistical thresholds are checked for conservativeness. It turns out, that corrections of the likelihood ratios in such finite-sample applications are required in order to avoid anti-conservative results.Author summaryStatistical methods based on the likelihood ratio are ubiquitous in mathematical modelling in systems biology. For example confidence intervals of estimated parameters rely on the statistical properties of the likelihood-ratio test. However, it is often overlooked that these intervals sizes rely on assumptions on the amounts of data, which are regularly violated in typical applications in systems biology. By checking the appropriateness of these assumptions in models from the literature, this study shows that in a surprisingly large fraction confidence intervals might be too small. Using a geometric interpretation of parameter estimation in the so-called data space, it is motivated why these issues appear and how they depend on the identifiability of the model parameters. In order to avoid such problematic situations, this work makes suggestions on how to adapt the statistical threshold values for likelihood-ratio test. By this, it can be assured that valid statistical conclusions are drawn from the analysis, also in situations where only smaller data sets are available. Such corrections yield for example more conservative confidence interval sizes and thus decrease a potential underestimation of the parameter uncertainty.
Integrated Drivers of Basal and Acute Immunity in Diverse Human Populations
Authors: Souquette Aisha , Allen E. Kaitlynn , Oshansky Christine M. , Tang Li , Wong Sook-san , Jeevan Trushar , Shi Lei , Pounds Stanley , Elias George , Kuan Guillermina , Balmaseda Angel , Zapata Raul , Shaw-Saliba Kathryn , Damme Pierre Van , Tendeloo Viggo Van , Dib Juan Carlos , Ogunjimi Benson , Webby Richard , Schultz-Cherry Stacey , Pekosz Andrew , Rothman Richard , Gordon Aubree , Thomas Paul G. 
Published: March 2023

AbstractPrior studies have identified genetic, infectious, and biological associations with immune competence and disease severity; however, there have been few integrative analyses of these factors and study populations are often limited in demographic diversity. Utilizing samples from 1,705 individuals in 5 countries, we examined putative determinants of immunity, including: single nucleotide polymorphisms, ancestry informative markers, herpesvirus status, age, and sex. In healthy subjects, we found significant differences in cytokine levels, leukocyte phenotypes, and gene expression. Transcriptional responses also varied by cohort, and the most significant determinant was ancestry. In influenza infected subjects, we found two disease severity immunophenotypes, largely driven by age. Additionally, cytokine regression models show each determinant differentially contributes to acute immune variation, with unique and interactive, location-specific herpesvirus effects. These results provide novel insight into the scope of immune heterogeneity across diverse populations, the integrative effects of factors which drive it, and the consequences for illness outcomes.
Multiple mechanisms of self-association of chemokine receptors CXCR4 and CCR5 demonstrated by deep mutagenesis
Authors: Gill Kevin S. , Mehta Kritika , Heredia Jeremiah D. , Krishnamurthy Vishnu V. , Zhang Kai , Procko Erik 
Published: March 2023

ABSTRACTChemokine receptors are members of the rhodopsin-like class A GPCRs whose signaling through G proteins drives the directional movement of cells in response to a chemokine gradient. Chemokine receptors CXCR4 and CCR5 have been extensively studied due to their roles in white blood cell development and inflammation and their status as coreceptors for HIV-1 infection, among other functions. Both receptors form dimers or oligomers but the function/s of self-associations are unclear. While CXCR4 has been crystallized in a dimeric arrangement, available atomic resolution structures of CCR5 are monomeric. To investigate the dimerization interfaces of these chemokine receptors, we used a bimolecular fluorescence complementation (BiFC)-based screen and deep mutational scanning to find mutations that modify receptor self-association. Many disruptive mutations promoted self-associations nonspecifically, suggesting they aggregated in the membrane. A mutationally intolerant region was found on CXCR4 that matched the crystallographic dimer interface, supporting this dimeric arrangement in living cells. A mutationally intolerant region was also observed on the surface of CCR5 by transmembrane helices 3 and 4. Mutations from the deep mutational scan that reduce BiFC were validated and were localized in the transmembrane domains as well as the C-terminal cytoplasmic tails where they reduced lipid microdomain localization. The reduced self-association mutants of CXCR4 had increased binding to the ligand CXCL12 but diminished calcium signaling. There was no change in syncytia formation with cells expressing HIV-1 Env. The data highlight that multiple mechanisms are involved in self-association of chemokine receptor chains.
Oxidation-sensitive cysteines drive IL-38 amyloid formation
Authors: Diaz-Barreiro Alejandro , Cereghetti Gea , Tonacini Jenna , Talabot-Ayer Dominique , Kieffer-Jaquinod Sylvie , Huard Arnaud , Swale Christopher , Couté Yohann , Peter Matthias , Francés-Monerris Antonio , Palmer Gaby 
Published: March 2023

AbstractCytokines of the interleukin (IL)-1 family are widely expressed in epithelial surfaces, including the epidermis, where they play a key role in the maintenance of barrier integrity and host defense. A recent report associated the IL-1 family member IL-33 with stress granules (SGs) in epithelial cells. Formation of SGs is promoted by the aggregation of proteins harboring low complexity regions (LCRs). In this study, using computational analyses, we predicted the presence of LCRs in six of the eleven IL-1 family members. Among these, IL-38 contained a long LCR and localized to Ras GTPase-activating protein binding protein 1 (G3BP1) positive SGs, as well as to G3BP1 negative intracellular protein condensates in keratinocytes exposed to oxidative stress (OS). In addition, we identified two highly aggregation-prone amyloid core (AC) motifs in the IL-38 LCR and detected the formation of amyloid IL-38 aggregates in response to OS in cells andin vitro. Disulfide bond mapping,in silicomodelling and the analysis of specific cysteine mutants supported a model in which specific oxidation-sensitive cysteines act as redox switches to modify the conformation of IL-38 and thus the surface exposure of its ACs, shuttling it from a soluble state into biomolecular condensates. Finally, the presence of IL-38 granules in human epidermal layers highly exposed to environmental OS suggests that oxidation-induced formation of amyloid aggregates, as a previously unrecognized intrinsic biological property of IL-38, may be physiologically relevant at this epithelial barrier.
Machine learning-based estimation of spatial gene expression pattern during ESC-derived retinal organoid development
Authors: Fujimura Yuki , Sakai Itsuki , Shioka Itsuki , Takata Nozomu , Hashimoto Atsushi , Funatomi Takuya , Okuda Satoru 
Published: March 2023

SummaryOrganoids, which can reproduce the complex tissue structures found in embryos, are revolutionizing basic research and regenerative medicine. In order to use organoids for research and medicine, it is necessary to assess the composition and arrangement of cell types within the organoid, i.e., spatial gene expression. However, current methods are invasive and require gene editing and immunostaining. In this study, we developed a non-invasive estimation method of spatial gene expression patterns using machine learning. A deep learning model was trained with an encoder-decoder architecture on a dataset of retinal organoids derived from mouse embryonic stem cells. This method successfully estimated spatially plausible fluorescent patterns with appropriate intensities, enabling the non-invasive, quantitative estimation of spatial gene expression patterns within each tissue. Thus, this method could lead to new avenues for evaluating spatial gene expression patterns across a wide range of biology and medicine fields.HighlightsA non-invasive estimation method of spatial gene expression pattern is proposedA CNN architecture is employed to convert a phase-contrast to fluorescence imageThe method was trained on a dataset of mouse ESC-derived retinal organoidsSpatially plausible patterns of Rx gene expressions were successfully estimated