bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial and temporal clustering of anti-SARS-CoV-2 antibodies in Illinois household cats, 2021-2023
Authors: Chen Chi , Martins Mathias , Nooruzzaman Mohammed , Yettapu Dipankar , Diel Diego G. , Reinhart Jennifer M. , Urbasic Ashlee , Robinson Hannah , Varga Csaba , Fang Ying 
Published: June 2023

ABSTRACTThis study evaluated the seroprevalence of SARS-CoV-2 antibodies in Illinois household cats from October 2021 to May 2023. Among 1,715 samples tested by serological assays, 244 samples (14%) tested positive. High-rate temporal, spatial, and space-time clusters of SARS-CoV-2 cases were assessed within 63 counties in Illinois. Three space-time clusters with higher than expected seroprevalence rates were identified in the northeastern, central-east, and southwest regions of Illinois, occurring between June and October 2022. Young cats had a higher seropositivity than older cats, and the third quarter of the year had the highest odds of seropositivity . This study provides an in-depth analysis of SARS-CoV-2 epidemiology in Illinois household cats, which will aid in COVID-19 control and prevention.Article summary lineSARS-CoV-2 antibody seroprevalence was assessed in Illinois domestic cats, in which a higher seropositivity rate was clustered in the northern, central, and southern Illinois regions with peak periods occurring between June and October 2022.
Characterizing personalized neuropathology in dementia and mild cognitive impairment with explainable artificial intelligence
Authors: Leonardsen Esten H. , Persson Karin , Grødem Edvard , Dinsdale Nicola , Schellhorn Till , Roe James M. , Vidal-Piñeiro Didac , Sørensen Øystein , Kaufmann Tobias , Westman Eric , Marquand Andre , Selbæk Geir , Andreassen Ole A. , Wolfers Thomas , Westlye Lars T. , Wang Yunpeng ,   the Alzheimer’s Disease Neuroimaging,   the Australian Imaging Biomarkers and Lifestyle flagship study of ageing
Published: June 2023

AbstractDeep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of neuropathology in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.
Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction
Authors: Bailey Neil W , Fulcher Ben D. , Caldwell Bridget , Hill Aron T , Fitzgibbon Bernadette , van Dijk Hanneke , Fitzgerald Paul B 
Published: June 2023

AbstractPrevious research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. Here we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67%,pFDR= 0.007), for which 405 features significantly distinguished meditators (allpFDR< 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR> 0.05). Our novel analysis approach suggests the key signatures of meditators’ brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.
Strong Genetic Overlaps Between Dimensional and Categorical Models of Bipolar Disorders in a Family Sample
Authors: Arbona-Lampaya Alejandro , Sung Heejong , D’Amico Alexander , Knowles Emma E. M. , Besançon Emily K. , Freifeld Ally , Lacbawan Ley , Lopes Fabiana , Kassem Layla , Nardi Antonio E. , McMahon Francis J. 
Published: June 2023

AbstractBackgroundBipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainly, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.MethodsParticipants in the Amish-Mennonite Bipolar Genetics (AMBiGen) study were assigned categorical mood disorder diagnoses by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment. Major MDQ dimensions were analyzed by Principal Component Analysis (PCA) in 726 participants. Heritability and genetic overlaps between categorical diagnoses and MDQ-derived dimensions were estimated with SOLAR-ECLIPSE within 432 genotyped participants.ResultsMDQ scores were significantly higher among individuals diagnosed with BD and related disorders, as expected, but varied widely among relatives. PCA suggested a three-component model for the MDQ. Heritability of the MDQ score was 30% (p<0.001), evenly distributed across its three principal components. Strong and significant genetic correlations were found between categorical diagnoses and most MDQ measures.LimitationsRecruitment through probands with BD resulted in increased prevalence of BD in this sample, limiting generalizability. Unavailable genetic data reduced sample size for some analyses.ConclusionSignificant heritability and high genetic correlations between categorical diagnoses and MDQ measures support a genetic continuity between dimensional and categorical models of BD.
Repeat investigation during social preference behavior is suppressed in male mice with prefrontal cortexcacna1c(Cav1.2)-deficiency through the dysregulation of neural dynamics
Authors: Hackett Jonathan , Nadkarni Viraj , Singh Ronak S. , Carthy Camille L. , Antigua Susan , Hall Baila S. , Rajadhyaksha Anjali M. 
Published: June 2023

AbstractImpairments in social behavior are observed in a range of neuropsychiatric disorders and several lines of evidence have demonstrated that dysfunction of the prefrontal cortex (PFC) plays a central role in social deficits. We have previously shown that loss of neuropsychiatric risk geneCacna1cthat codes for the Cav1.2 isoform of L-type calcium channels (LTCCs) in the PFC result in impaired sociability as tested using the three-chamber social approach test. In this study we aimed to further characterize the nature of the social deficit associated with a reduction in PFC Cav1.2 channels (Cav1.2PFCKOmice) by testing male mice in a range of social and non-social tests while examining PFC neural activity usingin vivoGCaMP6s fiber photometry. We found that during the first investigation of the social and non-social stimulus in the three-chamber test, both Cav1.2PFCKOmale mice and Cav1.2PFCGFPcontrols spent significantly more time with the social stimulus compared to a non-social object. In contrast, during repeat investigations while Cav1.2PFCWTmice continued to spend more time with the social stimulus, Cav1.2PFCKOmice spent equal amount of time with both social and non-social stimuli. Neural activity recordings paralleled social behavior with increase in PFC population activity in Cav1.2PFCWTmice during first and repeat investigations, which was predictive of social preference behavior. In Cav1.2PFCKOmice, there was an increase in PFC activity during first social investigation but not during repeat investigations. These behavioral and neural differences were not observed during a reciprocal social interaction test nor during a forced alternation novelty test. To evaluate a potential deficit in reward-related processes, we tested mice in a three-chamber test wherein the social stimulus was replaced by food. Behavioral testing revealed that both Cav1.2PFCWTand Cav1.2PFCKOmice showed a preference for food over object with significantly greater preference during repeat investigation. Interestingly, there was no increase in PFC activity when Cav1.2PFCWTor Cav1.2PFCKOfirst investigated the food however activity significantly increased in Cav1.2PFCWTmice during repeat investigations of the food. This was not observed in Cav1.2PFCKOmice. In summary, a reduction in Cav1.2 channels in the PFC suppresses the development of a sustained social preference in mice that is associated with lack of PFC neuronal population activity that may be related to deficits in social reward.
KRAB-zinc-finger proteins regulate endogenous retroviruses to sculpt germline transcriptomes and genome evolution
Authors: Otsuka Kai , Sakashita Akihiko , Maezawa So , Schultz Richard M. , Namekawa Satoshi H. 
Published: June 2023

AbstractAs transposable elements (TEs) coevolved with the host genome, the host genome exploited TEs as functional regulatory elements. What remains largely unknown are how the activity of TEs, namely, endogenous retroviruses (ERVs), are regulated and how TEs evolved in the germline. Here we show that KRAB domain-containing zinc-finger proteins (KZFPs), which are highly expressed in mitotically dividing spermatogonia, bind to suppressed ERVs that function following entry into meiosis as active enhancers. These features are observed for independently evolved KZFPs and ERVs in mice and humans, i.e., are evolutionarily conserved in mammals. Further, we show that meiotic sex chromosome inactivation (MSCI) antagonizes the coevolution of KZFPs and ERVs in mammals. Our study uncovers a mechanism by which KZFPs regulate ERVs to sculpt germline transcriptomes. We propose that epigenetic programming in the mammalian germline during the mitosis-to-meiosis transition facilitates coevolution of KZFPs and TEs on autosomes and is antagonized by MSCI.
An integrated mechanistic and data-driven computational model predicts cell responses to high- and low-affinity EGFR ligands
Authors: Myers Paul J. , Lee Sung Hyun , Lazzara Matthew J. 
Published: June 2023

ABSTRACTThe biophysical properties of ligand binding heavily influence the ability of receptors to specify cell fates. Understanding the rules by which ligand binding kinetics impact cell phenotype is challenging, however, because of the coupled information transfers that occur from receptors to downstream signaling effectors and from effectors to phenotypes. Here, we address that issue by developing an integrated mechanistic and data-driven computational modeling platform to predict cell responses to different ligands for the epidermal growth factor receptor (EGFR). Experimental data for model training and validation were generated using MCF7 human breast cancer cells treated with the high- and low-affinity ligands epidermal growth factor (EGF) and epiregulin (EREG), respectively. The integrated model captures the unintuitive, concentration-dependent abilities of EGF and EREG to drive signals and phenotypes differently, even at similar levels of receptor occupancy. For example, the model correctly predicts the dominance of EREG over EGF in driving a cell differentiation phenotype through AKT signaling at intermediate and saturating ligand concentrations and the ability of EGF and EREG to drive a broadly concentration-sensitive migration phenotype through cooperative ERK and AKT signaling. Parameter sensitivity analysis identifies EGFR endocytosis, which is differentially regulated by EGF and EREG, as one of the most important determinants of the alternative phenotypes driven by different ligands. The integrated model provides a new platform to predict how phenotypes are controlled by the earliest biophysical rate processes in signal transduction and may eventually be leveraged to understand receptor signaling system performance depends on cell context.One-sentence summaryIntegrated kinetic and data-driven EGFR signaling model identifies the specific signaling mechanisms that dictate cell responses to EGFR activation by different ligands.
Neural tube organoids self-organise floorplate through BMP-mediated cluster competition
Authors: Krammer Teresa , Stuart Hannah T. , Gromberg Elena , Ishihara Keisuke , Melchionda Manuela , Wang Jingkui , Costantini Elena , Lehr Stefanie , Cislo Dillon , Arbanas Laura , Hörmann Alexandra , Neumüller Ralph A. , Elvassore Nicola , Siggia Eric , Briscoe James , Kicheva Anna , Tanaka Elly M. 
Published: June 2023

AbstractThe neural tube (NT) has been a hallmark example of embryonic induction and patterning whereby the notochord induces an organiser, the floorplate, that secretes Sonic Hedgehog (SHH) to pattern the surrounding field of neural progenitors. On the other hand, NT organoids (NTOs) formed from embryonic stem cells (ESCs) undergo spontaneous floorplate formation and patterning in the absence of their normal embryonic inducers. Understanding how stem cells undergo regulative organiser formation is a central challenge in biology. Here, we investigated the self-organisation of a SHH-expressing floorplate organiser using clonal NTOs. Expression of FOXA2, a floorplate transcription factor, was initially spatially scattered before resolving into multiple clusters. These FOXA2+clusters underwent competition and physical sorting, resulting in a stable “winning” floorplate. We identified BMP signalling as a key governor of long-range cluster competition. FOXA2+clusters expressed BMP4 ligand suppressing FOXA2 in receiving cells, while simultaneously expressing the BMP-inhibitor NOGGIN to secure FOXA2+cluster survival. Genetic mutation ofNogginperturbed the floorplate not only in NTOs but alsoin vivoat the mid-hindbrain region of the mouse NT. These results demonstrate how the floorplate can form autonomously without its well-known inducer, the notochord, suggesting redundant mechanisms ensuring robustness. Defining molecular pathways that govern organiser self-organisation is critical in harnessing the developmental plasticity of stem cells toward directed tissue engineering.
Small allelic variants are a source of ancestral bias in structural variant breakpoint placement
Authors: Audano Peter A. , Beck Christine R. 
Published: June 2023

AbstractHigh-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥ 50 bp) has improved to near basepair precision. Despite these advances, many SVs in unique regions of the genome are subject to systematic bias that affects breakpoint location. This ambiguity leads to less accurate variant comparisons across samples, and it obscures true breakpoint features needed for mechanistic inferences. To understand why SVs are not consistently placed, we re-analyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identified variable breakpoints for 882 SV insertions and 180 SV deletions not anchored in tandem repeats (TRs) or segmental duplications (SDs). While this is unexpectedly high for genome assemblies in unique loci, we find read-based callsets from the same sequencing data yielded 1,566 insertions and 986 deletions with inconsistent breakpoints also not anchored in TRs or SDs. When we investigated causes for breakpoint inaccuracy, we found sequence and assembly errors had minimal impact, but we observed a strong effect of ancestry. We confirmed that polymorphic mismatches and small indels are enriched at shifted breakpoints and that these polymorphisms are generally lost when breakpoints shift. Long tracts of homology, such as SVs mediated by transposable elements, increase the likelihood of imprecise SV calls and the distance they are shifted. Tandem Duplication (TD) breakpoints are the most heavily affected SV class with 14% of TDs placed at different locations across haplotypes. While graph genome methods normalize SV calls across many samples, the resulting breakpoints are sometimes incorrect, highlighting a need to tune graph methods for breakpoint accuracy. The breakpoint inconsistencies we characterize collectively affect ∼5% of the SVs called in a human genome and underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoint placement, and increase the value of callsets for investigating mutational processes.
Robust estimation of brain stimulation evoked responses using magnetoencephalography
Authors: Oswal Ashwini , Abdi-Sargezeh Bahman , Özkurt Tolga Esat , Taulu Samu , Sarangmat Nagaraja , Green Alexander L , Litvak Vladimir 
Published: June 2023

AbstractMagnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, activity of interference sources may‘leak’into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large scale cortical networks.This technical report offers two contributions. Firstly, using phantom MEG recordings we describe an approach for validating the estimation accuracy of brain stimulation evoked responses. Secondly, we propose a novel denoising method for suppressing the leakage of stimulation related signal into recorded brain activity. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We highlight its advantages compared to the benchmark - spatiotemporal signal space separation (tSSS) - and show that it can more accurately reveal brain stimulation evoked responses.
Two independent DNA repair pathways cause mutagenesis in template switching deficientSaccharomyces cerevisiae
Authors: Jiang Yangyang Kate , Medley Eleanor , Brown Grant W. 
Published: June 2023

AbstractUpon DNA replication stress, cells utilize the post-replication repair pathway to repair single-stranded DNA and maintain genome integrity. Post-replication repair is divided into two branches: error-prone translesion synthesis, signaled by PCNA mono-ubiquitination, and error-free template switching, signaled by PCNA poly-ubiquitination. InSaccharomyces cerevisiae, Rad5 is involved in both branches of repair during DNA replication stress. When the PCNA poly-ubiquitination function of Rad5 is disrupted, Rad5 recruits translesion synthesis polymerases to stalled replication forks, resulting in mutagenic repair. Details of how mutagenic repair is carried out, as well as the relationship between Rad5-mediated mutagenic repair and the canonical PCNA-mediated mutagenic repair, remain to be understood. We find that Rad5-mediated mutagenic repair requires the translesion synthesis polymerase ζ but does not require other yeast translesion polymerase activities. Furthermore, we show that Rad5-mediated mutagenic repair is independent of PCNA binding by Rev1 and so is separable from canonical mutagenic repair. In the absence of error-free template switching, both modes of mutagenic repair contribute additively to replication stress response in a replication timing-independent manner. Cellular contexts where error-free template switching is compromised are not simply laboratory phenomena, as we find that a natural variant inRAD5is defective in PCNA poly-ubiquitination and therefore defective in error-free repair, resulting in Rad5- and PCNA-mediated mutagenic repair. Our results highlight the importance of Rad5 in regulating spontaneous mutagenesis and genetic diversity inS. cerevisiaethrough different modes of post-replication repair.
CaBLAM! A high-contrast bioluminescent Ca2+indicator derived from an engineeredOplophorus gracilirostrisluciferase
Authors: Lambert Gerard G. , Crespo Emmanuel L. , Murphy Jeremy , Boassa Daniela , Luong Selena , Celinskis Dmitrijs , Venn Stephanie , Nguyen Daniel K. , Hu Junru , Sprecher Brittany , Tree Maya O. , Orcutt Richard , Heydari Daniel , Bell Aidan B. , Torreblanca-Zanca Albertina , Hakimi Ali , Lipscombe Diane , Moore Christopher I. , Hochgeschwender Ute , Shaner Nathan C. 
Published: June 2023

AbstractCa2+plays many critical roles in cell physiology and biochemistry, leading researchers to develop a number of fluorescent small molecule dyes and genetically encodable probes that optically report changes in Ca2+concentrations in living cells. Though such fluorescence-based genetically encoded Ca2+indicators (GECIs) have become a mainstay of modern Ca2+sensing and imaging, bioluminescence-based GECIs—probes that generate light through oxidation of a small-molecule by a luciferase or photoprotein—have several distinct advantages over their fluorescent counterparts. Bioluminescent tags do not photobleach, do not suffer from nonspecific autofluorescent background, and do not lead to phototoxicity since they do not require the extremely bright extrinsic excitation light typically required for fluorescence imaging, especially with 2-photon microscopy. Current BL GECIs perform poorly relative to fluorescent GECIs, producing small changes in bioluminescence intensity due to high baseline signal at resting Ca2+concentrations and suboptimal Ca2+affinities. Here, we describe the development of a new bioluminescent GECI, “CaBLAM,” which displays much higher contrast (dynamic range) than previously described bioluminescent GECIs and has a Ca2+affinity suitable for capturing physiological changes in cytosolic Ca2+concentration. Derived from a new variant ofOplophorus gracilirostrisluciferase with superior in vitro properties and a highly favorable scaffold for insertion of sensor domains, CaBLAM allows for single-cell and subcellular resolution imaging of Ca2+dynamics at high frame rates in cultured neurons andin vivo. CaBLAM marks a significant milestone in the GECI timeline, enabling Ca2+recordings with high spatial and temporal resolution without perturbing cells with intense excitation light.