bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-omic spatial effects on high-resolution AI-derived retinal thickness
Authors: Jackson VE , Wu Y , Bonelli R , Owen J , Farashi S , Kihara Y , Gantner ML , Egan C , Williams KM , Ansell BRE , Tufail A , Lee AY , Bahlo M 
Published: August 2023

AbstractRetinal thickness is a marker of retinal health and more broadly, is seen as a promising biomarker for many systemic diseases. Retinal thickness measurements are procured from optical coherence tomography (OCT) as part of routine clinical eyecare. We processed the UK Biobank OCT images using a convolutional neural network to produce fine-scale retinal thickness measurements across >29,000 points in the macula, the part of the retina responsible for human central vision. The macula is disproportionately affected by high disease burden retinal disorders such as age-related macular degeneration and diabetic retinopathy, which both involve metabolic dysregulation. Analysis of common genomic variants, metabolomic, blood and immune biomarkers, ICD10 codes and polygenic risk scores across a fine-scale macular thickness grid, reveals multiple novel genetic loci-including four on the X chromosome; retinal thinning associated with many systemic disorders including multiple sclerosis; and multiple associations to correlated metabolites that cluster spatially in the retina. We highlight parafoveal thickness to be particularly susceptible to systemic insults. These results demonstrate the gains in discovery power and resolution achievable with AI-leveraged analysis. Results are accessible using a bespoke web interface that gives full control to pursue findings.Graphical Abstract
Recommended distances for physical distancing during COVID-19 pandemics reveal cultural connections between countries
Authors: Chai Dongwoo , El Mossadeq Layla , Raymond Michel , Courtier-Orgogozo Virginie 
Published: August 2023

AbstractDuring COVID-19 pandemic several public health measures were implemented by diverse countries to reduce the risk of COVID-19, including social distancing. Here we collected the minimal distance recommended by each country for physical distancing at the onset of the pandemic and aimed to examine whether it had an impact on the outbreak dynamics and how this specific value was chosen. Despite an absence of data on SARS-CoV-2 viral transmission at the beginning of the pandemic, we found that most countries recommended physical distancing with a precise minimal distance, between one meter/three feet and two meters/six feet. 45% of the countries advised one meter/three feet and 49% advised a higher minimal distance. The recommended minimal distance did not show a clear correlation with reproduction rate nor with the number of new cases per million, suggesting that the overall COVID-19 dynamics in each country depended on multiple interacting factors. Interestingly, the recommended minimal distance correlated with several cultural parameters: it was higher in countries with larger interpersonal distance between two interacting individuals in non-epidemic conditions, and it correlated with civil law systems, and with currency. This suggests that countries which share common conceptions such as civil law systems and currency unions tend to adopt the same public health measures.
Autoimmune inflammation triggers aberrant astrocytic calcium signaling to impair synaptic plasticity
Authors: Baraibar AM , Colomer T , Moreno-García A , Bernal-Chico A , Sánchez E , Utrilla C , Serrat R , Soria-Gómez E , Rodríguez-Antigüedad A , Araque A , Matute C , Marsicano G , Mato S 
Published: August 2023

AbstractCortical pathology involving inflammatory and neurodegenerative mechanisms is a hallmark of multiple sclerosis (MS) and a correlate of disease progression and cognitive decline. Astrocytes play a pivotal role in MS initiation and progression but astrocyte-neuronal network alterations contributing to gray matter pathology remain undefined. Here we measured astrocytic calcium in the experimental autoimmune encephalomyelitis (EAE) model of MS using fiber photometry in freely behaving mice and two-photon imagingex vivo. We identified the emergence of spontaneously hyperactive cortical astrocytes displaying calcium transients of increased duration as well as dysfunctional responses to cannabinoid, glutamate and purinoreceptor agonists during acute EAE disease. Deficits in astrocyte calcium responses are associated to abnormal signaling by Giand Gqprotein coupled receptors in the inflamed cortex and are partially mirrored in cells activated with pro-inflammatory factors bothin vitroandex vivothus suggesting cell-autonomous effects of the cortical neuroinflammatory environment. Finally, we show that deregulated astrocyte calcium activity is associated to an enhancement of glutamatergic gliotransmission and a shift of astrocyte-mediated short-term and long-term plasticity mechanisms towards synaptic potentiation. Overall our data identities astrocyte-neuronal network dysfunction as key pathological feature of the inflammatory gray matter that may contribute to MS symptomatology and clinical progression.
Central inhibition of Stearoyl-CoA Desaturase has minimal effects on the peripheral metabolic symptoms of the 3xTg Alzheimer’s disease mouse model
Authors: Hamilton Laura K. , Mbra Paule , Mailloux Sophia , Galoppin Manon , Aumont Anne , Fernandes Karl J.L. 
Published: August 2023

AbstractEvidence from genetic and epidemiological studies point to lipid metabolism defects in both the brain and periphery being at the core of Alzheimer’s disease (AD) pathogenesis. Previously, we reported that central inhibition of the rate-limiting enzyme in monounsaturated fatty acid synthesis, Stearoyl-CoA Desaturase (SCD), improves brain structure and function in the 3xTg mouse model of AD (3xTg-AD). Here, we tested whether these beneficial central effects involve recovery of peripheral metabolic defects, such as fat accumulation and glucose and insulin handling. As early as 3 months of age, 3xTg-AD mice exhibited obesity-like phenotypes including increased body weight and visceral and subcutaneous white adipose tissue deposition, as well as diabetic-like peripheral gluco-regulatory abnormalities. Intracerebral infusion of an SCD inhibitor that normalizes brain fatty acid metabolism, synapse loss and learning and memory deficits in middle-aged symptomatic 3xTg-AD mice did not affect peripheral phenotypes. This suggests that the beneficial effects of central SCD inhibition on cognitive function are not mediated by recovery of peripheral metabolic abnormalities. Given the widespread side-effects of systemically administered SCD inhibitors, these data suggest that selective inhibition of SCD in the brain may represent a clinically safer and more effective strategy for AD.
Cell adhesion marker expression dynamics during fusion of the optic fissure
Authors: Hardy Holly , Rainger Joe 
Published: August 2023

ABSTRACTTissue fusion is a critical process that is repeated in multiple contexts during embryonic development and shares common attributes to processes such as wound healing and metastases. Ocular coloboma is a developmental eye disorder that presents as a physical gap in the ventral eye, and is a major cause of childhood blindness. Coloboma results from fusion failure between opposing ventral retinal epithelia, but there are major knowledge gaps in our understanding of this process at the molecular and cell behavioural levels. Here we catalogue the expression of cell adhesion proteins: N-cadherin, E-cadherin, ZO-1, and the EMT transcriptional activator and cadherin regulator SNAI2. We find that fusion pioneer cells at the edges of the fusing optic fissure have unique and dynamic expression profiles for N-cad, E-cad and ZO-1, and that these are temporally preceded by expression of SNAI2. This highlights the unique properties of these cells and indicates that regulation of cell adhesion factors is a critical process in optic fissure closure.
Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings
Authors: LeRoy Nathan J. , Smith Jason P. , Zheng Guangtao , Rymuza Julia , Gharavi Erfaneh , Brown Donald E. , Zhang Aidong , Sheffield Nathan C. 
Published: August 2023

MotivationData from the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is now widely available. One major computational challenge is dealing with high dimensionality and inherent sparsity, which is typically addressed by producing lower-dimensional representations of single cells for downstream clustering tasks. Current approaches produce such individual cell embeddings directly through a one-step learning process. Here, we propose an alternative approach by building embedding models pre-trained on reference data. We argue that this provides a more flexible analysis workflow that also has computational performance advantages through transfer learning.ResultsWe implemented our approach in scEmbed, an unsupervised machine learning framework that learns low-dimensional embeddings of genomic regulatory regions to represent and analyze scATAC-seq data. scEmbed performs well in terms of clustering ability and has the key advantage of learning patterns of region co-occurrence that can be transferred to other, unseen datasets. Moreover, pre-trained models on reference data can be exploited to build fast and accurate cell-type annotation systems without the need for other data modalities. scEmbed is implemented in Python and it is available to download from GitHub. We also make our pre-trained models available on huggingface for public use.AvailabilityscEmbed is open source and available athttps://github.com/databio/geniml. Pre-trained models from this work can be obtained on huggingface:https://huggingface.co/databio.
Metabolic adjustments to winter severity in two geographically separated great tit (Parus major) populations
Authors: Pacioni Cesare , Bushuev Andrey , Sentís Marina , Kerimov Anvar , Ivankina Elena , Lens Luc , Strubbe Diederik 
Published: August 2023

AbstractUnderstanding the potential limits placed on organisms by their ecophysiology is crucial for predicting their responses to varying environmental conditions. Studies to date have traditionally relied on between-species comparisons, however, recently, there has been a growing recognition of the importance of intraspecific variation in shaping an organism’s ecological and physiological responses. In this context, widely distributed resident bird species offer a well-suited study system to examine intraspecific geographical variation in ecophysiological traits. A main hypothesis for explaining avian thermoregulatory mechanisms is the aerobic capacity model, which posits a positive correlation between basal (BMR) and summit (Msum) metabolism, caused by the energetic maintenance costs associated with increased muscle mass for shivering thermogenesis and enhanced investment in digestive organs for food processing. Most evidence for this hypothesis, however, comes from interspecific comparisons only, and the ecophysiological underpinnings of avian thermoregulatory capacities hence remain controversial. Here, we focus on great tits (Parus major), measuring winter BMR and Msumin two populations from different climates, a maritime-temperate (Gontrode, Belgium) and a continental (Zvenigorod, Russia) one. We test for the presence of intraspecific geographical variation in metabolic rates and assess the predictions following the aerobic capacity model. We found that metabolic rates differed between populations, whereby the birds from the maritime-temperate climate (Gontrode) showed higher (whole-body and mass-independent) BMR whereas conversely, great tits from Zvenigorod showed higher levels of both (whole-body and mass-independent) Msum. Within each population, our data did not fully support the aerobic capacity model’s predictions. We argue that the decoupling of BMR and Msumobserved may be caused by different selective forces acting on these metabolic rates, with birds from the continental-climate Zvenigorod population facing the need to conserve energy for surviving long winter nights (by keeping their BMR at low levels) while simultaneously being able to generate more heat (i.e., a high Msum) to withstand cold spells. We argue that the coupling or uncoupling of basal and maximum metabolic rates at the intraspecific level is likely influenced by different selective pressures that shape local adaptations in response to different climate regimes.
Scaling between cell cycle duration and wing growth is regulated by Fat-Dachsous signaling inDrosophila
Authors: Liu Andrew , O’Connell Jessica , Wall Farley , Carthew Richard W. 
Published: August 2023

AbstractThe atypical cadherins Fat and Dachsous (Ds) signal through the Hippo pathway to regulate growth of numerous organs, including theDrosophilawing. Here, we find that Ds-Fat signaling tunes a unique feature of cell proliferation found to control the rate of wing growth during the third instar larval phase. The duration of the cell cycle increases in direct proportion to the size of the wing, leading to linear-like growth during the third instar. Ds-Fat signaling enhances the rate at which the cell cycle lengthens with wing size, thus diminishing the rate of wing growth. We show that this results in a complex but stereotyped relative scaling of wing growth with body growth inDrosophila. Finally, we examine the dynamics of Fat and Ds protein distribution in the wing, observing graded distributions that change during growth. However, the significance of these dynamics is unclear since perturbations in expression have negligible impact on wing growth.
In silicoassessment of 18S rDNA metabarcoding markers for the characterization of nematode communities
Authors: Ficetola Gentile Francesco , Guerrieri Alessia , Cantera Isabel , Bonin Aurelie 
Published: August 2023

AbstractNematodes are keystone actors of soil, freshwater and marine ecosystems, but the complexity of morphological identification has limited broad-scale monitoring of their biodiversity. DNA metabarcoding is increasingly used to assess nematode biodiversity but requires universal primers with high taxonomic coverage and high taxonomic resolution. Several primers have been proposed for the metabarcoding of nematode diversity, many of which target the 18S rRNA gene.In-silicoanalyses have a great potential to assess key parameters of primers, including their taxonomic coverage, resolution and specificity. Based on a recently-available reference database, we testedin-silicothe performance of fourteen commonly used and one newly optimized primer for nematode metabarcoding. Most primers showed very good coverage, as amplified most of sequences in the reference database, while four markers showed limited coverage. All primers showed good taxonomic resolution. Resolution was particularly good if the aim was the identification of higher-level taxa, such as genera or families. Overall, species-level resolution was higher for primers amplifying long fragments. None of the primers was highly specific for nematodes as, despite some variation, they all amplified a large number of other eukaryotes. Differences in performance across primers highlight the complexity of the choice of markers appropriate for the metabarcoding of nematodes, which depends on a trade-off between taxonomic resolution and the length of amplified fragments. Ourin-silicoanalyses provide new insights for the identification of most appropriate primers, depending on the study goals and the origin of DNA samples. This represents an essential step to design and optimize metabarcoding studies assessing nematode diversity.
Systematic characterization of therapeutic vulnerabilities in Multiple Myeloma with Amp1q reveals increased sensitivity to the combination of MCL1 and PI3K inhibitors
Authors: Sklavenitis-Pistofidis Romanos , Lightbody Elizabeth D. , Reidy Mairead , Tsuji Junko , Aranha Michelle P. , Heilpern-Mallory Daniel , Huynh Daisy , Chong Stephen J. F. , Hackett Liam , Haradhvala Nicholas J. , Wu Ting , Su Nang K. , Berrios Brianna , Alberge Jean-Baptiste , Dutta Ankit , Davids Matthew S. , Papaioannou Maria , Getz Gad , Ghobrial Irene M. , Manier Salomon 
Published: August 2023

SUMMARYThe development of targeted therapy for patients with Multiple Myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chr1q (Amp1q) is the most frequent arm-level copy number gain in patients with MM, and it is associated with higher risk of progression and death despite recent advances in therapeutics. Thus, developing targeted therapy for patients with MM and Amp1q stands to benefit a large portion of patients in need of more effective management. Here, we employed large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with Amp1q and showed increased sensitivity to the combination of MCL1 and PI3K inhibitors. Using single-cell RNA sequencing, we compared subclones with and without Amp1q within the same patient tumors and showed that Amp1q is associated with higher levels ofMCL1and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number for part of the chr1q arm, we showed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with Amp1q.
Plant-mediated effects of fire and fragmentation drive plant-pollinator interaction β-diversity in fire-dependent pine savannas
Authors: Moreno-García Pablo , Freeman Johanna E. , Campbell Joshua W. , Broadbent Eben N. , Almeyda Zambrano Angélica M. , Prata Gabriel , de Almeida Danilo R. A. , Gilb Scott , Baiser Benjamin 
Published: August 2023

ABSTRACTInteraction β-diversity is an essential measure to understand and conserve species interactions and ecosystem functioning. Interaction β-diversity explains the variation in species interactions across spatial and temporal gradients, resulting from species turnover or interaction rewiring. Each component of interaction β-diversity has different ecological implications and practical consequences. While interaction β-diversity due to species turnover is related to assembly processes and fragmentation, rewiring can support high biodiversity and confer resilience to ecological networks. Despite this, it is unclear whether both components respond to the same or different ecological drivers. Here, we assessed the ecological drivers of plant-pollinator interaction β-diversity and its components across 24 sites in 9 Longleaf Pine (LLP) savannas in north and central Florida. We evaluated the effects of flowering plant composition and flower abundance, vegetation, fire regime, soil moisture, terrain characteristics, climate, spatial context, and geographic location. We used path analysis to evaluate the drivers of spatial interaction β-diversity and its main components. We then used generalized linear mixed models to assess the temporal patterns of spatial β-diversity among sites within preserves. We found that plant-pollinator networks in LLP savannas are highly variable across space and time, mainly due to species turnover and possibly in response to abiotic gradients and dispersal boundaries. Flower abundance and flowering plant composition, geographic location, fire seasonality, soil moisture, and landscape context were the main drivers of plant-pollinator β-diversity, highlighting the role of fire management and habitat connectivity in preserving plant-pollinator networks.
Deep Learning-Enabled, Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry
Authors: Vora Nilay , Shekar Prashant , Esmail Michael , Patra Abani , Georgakoudi Irene 
Published: August 2023

AbstractMetastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs representing an increased risk factor for metastasis. Current detection platforms are optimized forex vivodetection of CTCs only. Microfluidic chips and size exclusion methods have been proposed for CTCC detection; however, they lackin vivoutility and real-time monitoring capability. Confocal backscatter and fluorescence flow cytometry (BSFC) has been used for label-free detection of CTCCs in whole blood based on machine learning (ML) enabled peak classification. Here, we expand to a deep-learning (DL) -based, peak detection and classification model to detect CTCCs in whole blood data. We demonstrate that DL-based BSFC has a low false alarm rate of 0.78 events/min with a high Pearson correlation coefficient of 0.943 between detected events and expected events. DL-based BSFC of whole blood maintains a detection purity of 72% and a sensitivity of 35.3% for both homotypic and heterotypic CTCCs starting at a minimum size of two cells. We also demonstrate through artificial spiking studies that DL-based BSFC is sensitive to changes in the number of CTCCs present in the samples and does not add variability in detection beyond the expected variability from Poisson statistics. The performance established by DL-based BSFC motivates its use forin vivodetection of CTCCs. Further developments of label-free BSFC to enhance throughput could lead to critical applications in the clinical detection of CTCCs andex vivoisolation of CTCC from whole blood with minimal disruption and processing steps.
Genetic regulatory effects in response to a high cholesterol, high fat diet in baboons
Authors: Lin Wenhe , Wall Jeffrey D. , Li Ge , Newman Deborah , Yang Yunqi , Abney Mark , VandeBerg John L. , Olivier Michael , Gilad Yoav , Cox Laura A. 
Published: August 2023

SummarySteady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWAS), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using nonhuman primate models.