bluuebunny/crossref_metadata_2025_split huggingface dataset:
Translation of Immunomodulatory Therapy to Treat Chronic Heart Failure: Preclinical Studies to First in Human
Authors: Humes H. David , Aaronson Keith D. , Buffington Deborah , Sabbah Hani N. , Westover Angela J. , Yessayan Lenar T. , Szamosfalvi Balazs , Pagani Francis D. 
Published: August 2022

ABSTRACTThe objective of this study was to evaluate the use of an extracorporeal immunomodulatory device on the immune dysregulated state of chronic heart failure (CHF). Inflammation has been associated with progression and complications of CHF but no effective therapy has yet been identified to treat this dysregulated immunologic state. The selective cytopheretic device (SCD) provides extracorporeal autologous cell processing to lessen the inflammatory activity of circulating leukocytes of the innate immunologic system. SCD treatment in a canine model of systolic CHF diminished leukocyte inflammatory activity and enhanced cardiac performance as measured by left ventricular (LV) ejection fraction and myocardial contractility by stroke volume (SV) up to 4 weeks after treatment initiation. Translation of these observations in first in human, proof of concept clinical study was evaluated in a patient with severe systolic CHF ineligible for cardiac transplantation or left ventricular assist device (LVAD) due to renal insufficiency and right ventricular dysfunction. Six hour SCD treatments over 6 consecutive days resulted in selective removal of inflammatory neutrophils and monocytes and reduction in key plasma cytokines, including tumor necrosis factor (TNF)-a, interleukin (IL)-6, IL-8, monocyte chemoattractant protein (MCP)-1. These immunologic changes were associated with significant improvements in cardiac power output, right ventricular stroke work index, cardiac index and LVSV index, stabilization of renal function with progressive volume removal permitted successful LVAD implantation. This translational research study demonstrates a promising immunomodulatory approach to improve cardiac performance in systolic CHF and supports the important role of inflammation in the progression of CHF.
Rapidly shifting immunologic landscape and severity of SARS-CoV-2 in the Omicron era in South Africa
Authors: Sun Kaiyuan , Tempia Stefano , Kleynhans Jackie , Gottberg Anne von , McMorrow Meredith L , Wolter Nicole , Bhiman Jinal N. , Moyes Jocelyn , Carrim Maimuna , Martinson Neil A , Kahn Kathleen , Lebina Limakatso , du Toit Jacques D. , Mkhencele Thulisa , Viboud Cécile , Cohen Cheryl ,   the PHIRST group
Published: August 2022

AbstractSouth Africa was among the first countries to detect the SARS-CoV-2 Omicron variant. Propelled by increased transmissibility and immune escape properties, Omicron displaced other globally circulating variants within 3 months of its emergence. Due to limited testing, Omicron’s attenuated clinical severity, and an increased risk of reinfection, the size of the Omicron BA.1 and BA.2 subvariants (BA.1/2) wave remains poorly understood in South Africa and in many other countries. Using South African data from urban and rural cohorts closely monitored since the beginning of the pandemic, we analyzed sequential serum samples collected before, during, and after the Omicron BA.1/2 wave to infer infection rates and monitor changes in the immune histories of participants over time. Omicron BA.1/2 infection attack rates reached 65% (95% CI, 60% – 69%) in the rural cohort and 58% (95% CI, 61% – 74%) in the urban cohort, with repeat infections and vaccine breakthroughs accounting for >60% of all infections at both sites. Combined with previously collected data on pre-Omicron variant infections within the same cohorts, we identified 14 distinct categories of SARS-CoV-2 antigen exposure histories in the aftermath of the Omicron BA.1/2 wave, indicating a particularly fragmented immunologic landscape. Few individuals (<6%) remained naïve to SARS-CoV-2 and no exposure history category represented over 25% of the population at either cohort site. Further, cohort participants were more than twice as likely to get infected during the Omicron BA.1/2 wave, compared to the Delta wave. Prior infection with the ancestral strain (with D614G mutation), Beta, and Delta variants provided 13% (95% CI, -21% – 37%), 34% (95% CI, 17% – 48%), and 51% (95% CI, 39% – 60%) protection against Omicron BA.1/2 infection, respectively. Hybrid immunity (prior infection and vaccination) and repeated prior infections (without vaccination) reduced the risks of Omicron BA.1/2 infection by 60% (95% CI, 42% – 72%) and 85% (95% CI, 76% – 92%) respectively. Reinfections and vaccine breakthroughs had 41% (95% CI, 26% – 53%) lower risk of onward transmission than primary infections. Our study sheds light on a rapidly shifting landscape of population immunity, along with the changing characteristics of SARS-CoV-2, and how these factors interact to shape the success of emerging variants. Our findings are especially relevant to populations similar to South Africa with low SARS-CoV-2 vaccine coverage and a dominant contribution of immunity from prior infection. Looking forward, the study provides context for anticipating the long-term circulation of SARS-CoV-2 in populations no longer naïve to the virus.
Seasonal polyphenism underlies the origin of a sterile caste in aphids
Authors: Uematsu Keigo , Kutsukake Mayako , Shigenobu Shuji , Yang Man-Miao , Shibao Harunobu , Fukatsu Takema 
Published: August 2022

AbstractThe origin of a sterile caste among eusocial animals has been a fundamental but still unresolved problem in understanding the evolution of biological complexity. At the origin of a sterile caste, recruitment of pre-existing plasticity may lead to produce physiologically, morphologically and behaviorally distinct caste phenotypes. Here, we provide convincing evidence that preexisting seasonal polyphenism has been recruited to generate a sterile soldier caste in host-alternating social aphids. We demonstrate that sterile soldier nymphs of Colophina aphids resemble those of monomorphic defensive nymphs produced in a different host-plant generation. Notably, the two morphs in the basal species show the closest similarity in morphology and gene expression among all morph pairs. Moreover, their evolutionary phenotypic changes along the phylogeny of four Colophina species are significantly correlated positively. These results suggest that they may share the common regulatory mechanisms of development, which underpin the heterochronic expression of monomorphic defenders on the different host plant leading to the evolution of a novel soldier phenotype. We further demonstrate that the monomorphic defenders can increase their inclusive fitness by killing predator’s eggs on a seasonally different host plant. Taken together, our findings suggest that preexisting plasticity that can gain indirect fitness benefits facilitates the early evolution of a sterile caste.
Deciphering the Evolutionary History of Complex Rearrangements in Head and Neck Cancer Patients Using Multi-Omic Approach
Authors: Chae Jeesoo , Lee Jin Seok , Park Jongkeun , Lee Dong-Sung , Park Weon Seo , Clock Benjamin , Dixon Jesse R. , Jung Yuh-Seog , Hong Dongwan 
Published: August 2022

ABSTRACTDespite the large efforts in international cancer genome consortium studies, there are still a large proportion of tumors with complex genomic rearrangement often remained without a clinically relevant molecular characterization. Integration of multi-omic data helps elucidating evolutionary history of such cases and identifying predictive molecular markers. Here we present the findings of our proof-of-principle study that investigated the evolutionary history of complex rearrangements in primary head and neck tumor genomes integrating long-read whole-genome, Hi-C, and RNA sequencing. We report a HPV-positive case with development of complex genomic rearrangements tracing back to HPV-mediated genomic instability and a HPV-negative case with an enhancer hi-jacking in a region of chromothripsis predicted to co-occur with a neoloop and a super-enhancer. These structural alterations resulted in overexpression of the oncogenes CCND1 and ALK, respectively, validated with immunohistochemistry assay. Furthermore, we introduce a novel analytic approach utilizing long-read whole-genome data distinguishing somatic mutations before and after structural variants. Our findings highlight the need for multi-modal sequencing strategies to increase our understanding of cancer evolution and rare biomarkers in poorly understood cancers.
Development of a multi-sensor integrated midbrain organoid-on-a-chip platform for studying Parkinson’s disease
Authors: Spitz Sarah , Bolognin Silvia , Brandauer Konstanze , Füßl Julia , Schuller Patrick , Schobesberger Silvia , Jordan Christian , Schädl Barbara , Grillari Johannes , Wanzenboeck Heinz D. , Mayr Torsten , Harasek Michael , Schwamborn Jens C. , Ertl Peter 
Published: August 2022

AbstractDue to its ability to recapitulate key pathological processes in vitro, midbrain organoid technology has significantly advanced the modeling of Parkinson’s disease over the last few years. However, some limitations such as insufficient tissue differentiation and maturation, deficient nutrient supply, and low analytical accessibility persist, altogether restricting the technology from reaching its full potential. To overcome these drawbacks, we have developed a multi-sensor integrated organ-on-a-chip platform capable of monitoring the electrophysiological, respiratory, and dopaminergic activity of human midbrain organoids. Our study showed that microfluidic cultivation resulted in a marked reduction in necrotic core formation, improved tissue differentiation as well as the recapitulation of key pathological hallmarks. Non-invasive monitoring employing an orthogonal sensing strategy revealed a clear time dependency in the onset of Parkinson’s disease-related phenotypes, reflecting the complex progression of the neurodegenerative disorder. Furthermore, drug-mediated rescue effects were observed after treatment with the repurposed compound 2-hydroxypropyl β-cyclodextrin, highlighting the platform’s potential in the context of drug screening applications as well as personalized medicine.
Investigating the human and non-obese diabetic mouse MHC class II immunopeptidome using protein language modelling
Authors: Hartout Philip , Počuča Bojana , Méndez-García Celia , Schleberger Christian 
Published: August 2022

AbstractIdentifying peptides associated with the major histocompability complex class II (MHCII) is a central task in the evaluation of the immunoregulatory function of therapeutics and drug prototypes. MHCII-peptide presentation prediction has multiple biopharmaceutical applications, including the safety assessment of biologics and engineered derivativesin silico, or the fast progression of antigen-specific immunomodulatory drug discovery programs in immune disease and cancer. This has resulted in the collection of large-scale data sets on adaptive immune receptor antigenic responses and MHC-associated peptide proteomics. In parallel, recent deep learning algorithmic advances in protein language modelling (PLM) have shown potential in leveraging large collections of sequence data and improve MHC presentation prediction. Here, we train a compact transformer model (AEGIS) on human and mouse MHCII immunopeptidome data, including a preclinical murine model, and evaluate its performance on the peptide presentation prediction task. We show that the transformer performs on par with existing deep learning algorithms and that combining datasets from multiple organisms increases model performance. We trained variants of the model with and without MHCII information. In both alternatives, the inclusion of peptides presented by the I-Ag7MHC class II molecule expressed by the non-obese diabetic (NOD) mice enabled for the first time the accuratein silicoprediction of presented peptides in a preclinical type 1 diabetes model organism, which has promising therapeutic applications.0.1Availability and implementationThe source code is available athttps://github.com/Novartis/AEGIS.
Hypocretin/orexin neurons encode social discrimination and exhibit a sex-dependent necessity for social interaction
Authors: Dawson Matthew , Terstege Dylan J , Jamani Naila , Tsutsui Mio , Pavlov Dmitrii , Bugescu Raluca , Epp Jonathan R , Leinninger Gina M , Sargin Derya 
Published: August 2022

SummaryIntraspecies social interactions are integral for survival and maintenance of society among all mammalian species. Yet, our understanding of the neural systems and mechanisms involved in the establishment of social connectedness are limited. Since their initial discovery as regulators of sleep/wakefulness and appetite in the brain, the hypocretin/orexin neurons have also been shown to play an essential role in modulating energy homeostasis, motivated and emotional behavior. These neurons are located exclusively in the hypothalamus which, regulates complex and goal-directed behaviors. The hypothalamus also plays an important role in the modulation of social behavior by encoding internal states. However, our understanding of the role of hypocretin neurons in social behavior is currently limited. To address this knowledge gap, we performed a combination of fiber photometry and machine learning based behavioral analysis in female and male mice expressing GCaMP6s in hypocretin neurons. We then applied optogenetic and pharmacological inhibition of hypocretin neuron signaling to determine the necessity of the hcrt neuron population for social behavior. Our results indicate that hypocretin neurons exhibit a robust increase in activity in response to social interaction in both female and male mice. We show here for the first time a social discrimination signal that is encoded differentially by hcrt neurons based on the nature of the social encounter. The intensity of the hcrt neuron activity predicts the subsequent duration of social interaction. The optogenetic inhibition of hypocretin neuron activity during social behavior leads to a reduction in the amount of time mice are engaged in social interaction in males but not in females. Blocking hcrt1 (orexin 1) receptors similarly reduces social interaction in males only. Reduced hcrt1 receptor signaling results in increased activity in the insular cortex and reduced activity in the VTA after social interaction in male mice. Together, these data implicate the lateral hypothalamus hypocretin neurons as a sexually dimorphic key regulator within the larger network of neural systems involved in social behavior. Our findings carry significant implications for the treatment of neuropsychiatric diseases characterized by social dysfunction, particularly considering the varying prevalence observed across different sexes.
Estimating Waiting Distances Between Genealogy Changes under a Multi-Species Extension of the Sequentially Markov Coalescent
Authors: McKenzie Patrick F. , Eaton Deren A. R. 
Published: August 2022

AbstractGenomes are composed of a mosaic of segments inherited from different ancestors, each separated by past recombination events. Consequently, genealogical relationships among multiple genomes vary spatially across different genomic regions. Expectations for the amount of genealogical variation among unlinked (uncorrelated) genomic regions is well described for either a single population (coalescent) or multiple structured populations (multispecies coalescent). However, the expected similarity among genealogies at linked regions of a genome is less well characterized. Recently, an analytical solution was derived for the expected distribution of waiting distances between changes in genealogical trees spatially across a genome for a single population with constant effective population size. Here we describe a generalization of this result, in terms of the expected distribution of waiting distances between changes in genealogical trees and topologies, for multiple structured populations with branch-specific effective population sizes (i.e., under the multispecies coalescent). Our solutions establish an expectation for genetic linkage in multispecies datasets and provide a new likelihood framework for linking demographic models with local ancestry inference across genomes.
Herbarium records provide reliable phenology estimates in the understudied tropics
Authors: Park Daniel S. , Lyra Goia M. , Ellison Aaron M. , Maruyama Rogério Katsuhito Barbosa , Torquato Débora dos Reis , Asprino Renata C. , Cook Benjamin I. , Davis Charles C. 
Published: August 2022

AbstractPlant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of particular concern are tropical biomes, which represent the most biodiverse and imperiled regions of the world. However, compared to temperate floras, we know little about phenological responses of tropical plants because long-term observational datasets from the tropics are sparse.Herbarium specimens have greatly increased our phenological knowledge in temperate regions, but similar data have been underutilized in the tropics and their suitability for this purpose has not been broadly validated. Here, we compare phenological estimates derived from field observational data (i.e., plot surveys) and herbarium specimens at various spatial and taxonomic scales to determine whether specimens can provide accurate estimations of reproductive timing and its spatial variation.Here we demonstrate that phenological estimates from field observations and herbarium specimens coincide well. Fewer than 5% of the species exhibited significant differences between flowering periods inferred from field observations versus specimens regardless of spatial aggregation. In contrast to studies based on field records, herbarium specimens sampled much larger geographic and climatic ranges, as has been documented previously for temperate plants, and effectively captured phenological responses across varied environments.Herbarium specimens are verified to be a vital resource for closing the gap in our phenological knowledge of tropical systems. Tropical plant reproductive phenology inferred from herbarium records are widely congruent with field observations, suggesting that they can (and should) be used to investigate phenological variation and their associated environmental cues more broadly across tropical biomes.
Prediction of SUMOylation targets in Drosophila melanogaster
Authors: Ramtirtha Yogendra , Madhusudhan M. S. 
Published: August 2022

ABSTRACTSUMOylation is a post translational modification that involves covalent attachment of SUMO C-terminus to side chain amino group of lysine residues in target proteins. Disruption of the modification has been linked to neurodegenerative diseases and cancer. Recent improvements in mass spectrometry-coupled proteomics experiments have enabled high-throughput identification of SUMOylated lysines in mammalian cells. One such study was Hendriks et al, 2018, wherein the authors identified SUMOylated lysines in human and mouse cells. Information from this study was used as an input to a sequence homology based method to annotate putative SUMOylatable lysines from the proteome of fruit flyDrosophila melanogaster. 5283 human and 468 mouse SUMOylated proteins led to the identification of 8539 and 1700 fly homologs and putative SUMOylation sites therein respectively. Clustering analysis was carried out on these annotated sites to obtain three typs of information. First type of information revealed amino acid preferences in the local sequence vicinity of the annotated sites. This exercise confirmed that ψ – K – x – (E/D) where ψ = I/V/L, is the most frequently occurring sequence motif involving SUMOylated lysines.Second type of information revealed protein families that contain the annotated sites. Results from this exercise reveal that members of thousands of protein families contain annotated SUMOylation sites. Third type of information revealed preferred biological and cellular functions of proteins containing the annotated lysines. This exercise revealed that nucleus and transcription are preferred cellular localization and biological function respectively.
Neural processing of goal and non-goal-directed movements on the smartphone
Authors: Kock Ruchella , Ceolini Enea , Groenewegen Lysanne , Ghosh Arko 
Published: August 2022

AbstractThe discrete behavioral events captured on the smartphone touchscreen may help unravel real-world neural processing. We find that neural signals (EEG) surrounding a touchscreen event show peculiarly contralateral motor preparation, visual processing, and the consolidation of information. We leveraged these events in conjunction with kinematic recordings of the thumb and an artificial neural network to separate highly similar movements according to whether they resulted in a smartphone touch (goal-directed) or not (non-goal-directed). Despite their kinematic similarity underscored by the model, the signatures of neural control of movement and the post-movement processing were substantially dampened for the non-goal-directed movements, and these movements uniquely evoked error-related signals. We speculate that these unnecessary movements are common in the real world and although inconsequential the brain still provides limited motor preparation and tracks the action outcome. Real-world behavior is composed of neural processes that are difficult to capture in conventional laboratory-based tasks.
SpatialDM: Rapid identification of spatially co-expressed ligand-receptor reveals cell-cell communication patterns
Authors: Li Zhuoxuan , Wang Tianjie , Liu Pengtao , Huang Yuanhua 
Published: August 2022

AbstractCell-cell communication is a key aspect of dissecting the complex cellular microenvironment. Existing single-cell and spatial transcriptomics-based methods primarily focus on identifying cell-type pairs for a specific interaction, while less attention has been paid to the prioritisation of interaction features or the identification of interaction spots in the spatial context. Here, we introduce SpatialDM, a statistical model and toolbox leveraging a bivariant Moran’s statistic to detect spatially co-expressed ligand and receptor pairs, their local interacting spots (single-spot resolution), and communication patterns. By deriving an analytical null distribution, this method is scalable to millions of spots and shows accurate and robust performance in various simulations. On multiple datasets including melanoma, Ventricular–Subventricular Zone (SVZ), and intestine, SpatialDM reveals promising communication patterns and identifies differential interactions between conditions, hence enabling the discovery of context-specific cell cooperation and signalling.