bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiplicative frequency and angular speckle reduction in ultrasound imaging
Authors: Li Yilei , Toyonaga Noah , Jiang James , Cable Alex , Chu Steven 
Published: November 2023

AbstractSpeckle is the major artifact in ultrasound imaging, and it is well-known that speckle can be reduced by compounding (averaging) images taken either at different frequencies or from different angles. By averaging images of a phantom taken over a frequency rangeand a 90° span of angles, the combined speckle reduction is demonstrated to be ~ 9× compared to non-compounded images, while the reduction with frequency or angle averaging resulted in reductions of ~ 3× individually. The rf input to the transducer is altered to vary the sound frequency and the phantom is rotated with respect to the transducer to obtain different imaging angles. Numerical simulations of sound scattered by randomly distributed point scatterers showed quantitative agreement with the experiment. Using a commercial system, a 6× reduction in speckle is demonstrated imaging a human wrist. A robot arm is used to move the transducer along a circular path to acquire images at 9 angles separated by 10°. The commercial system does not allow direct control of the input to the transducer, so the broadband signal detected is Fourier filtered to obtain images at different frequencies with ~ 2× reduced frequency range. Images taken at different angles contain distortions from speed of sound variations and pressure induced by the probe. Two forms of non-rigid image registration are applied to correct for the distortions and create a higher resolution composite image. A design for achieving ~10× speckle reduction with essentially no loss in imaging speed is described.
Pericyte ablation causes hypoactivity and reactive gliosis in adult mice
Authors: Cashion Jake M. , Brown Lachlan S. , Morris Gary P. , Fortune Alastair J. , Courtney Jo-Maree , Cullen Carlie L. , Young Kaylene M. , Sutherland Brad A. 
Published: November 2023

AbstractPericytes are contractile cells that enwrap capillaries allowing them to control blood flow, maintain the blood-brain barrier and regulate immune cell trafficking in the CNS. Pericytes are lost or become dysfunctional in neurodegenerative diseases such as Alzheimer’s disease, stroke, and multiple sclerosis, but their role in health and disease is poorly understood. Our aim was to evaluate blood-brain barrier integrity and glial reactivity, and to assess behavioural phenotypes that emerge following pericyte ablation in adult mice. The delivery of tamoxifen toPDGFRβ-CreERT2:: Rosa26-DTAtransgenic mice produced a dose-dependent ablation of pericytes. A single low dose of tamoxifen ablated approximately half of all brain pericytes, and two consecutive daily high doses ablated more than 80% of brain pericytes. To determine whether pericyte ablation could induce a behavioural phenotype, we assessed patterns of voluntary movement, as well as balance and coordination using the open field and beam walk tasks. Mice with ∼50% pericyte loss travelled half the distance and spent half as much time moving in the open field as control mice. Mice with more than 80% pericyte ablation also slipped more frequently in the beam walk task than control mice. In brain cryosections from pericyte-ablated mice, blood vessel structure was unchanged, but lumen area was increased. Pericyte-ablated mice also experienced blood-brain barrier leakage, hypoxia and increased microgliosis and astrogliosis compared to control mice. Our results highlight the importance of pericytes for brain health, as pericyte loss can directly drive brain injury and behavioural alterations in mice.
Reliance on self-reports and estimated food composition data in nutrition research introduces significant bias that can only be addressed with biomarkers
Authors: Ottaviani Javier I. , Sagi-Kiss Virag , Schroeter Hagen , Kuhnle Gunter G. C. 
Published: November 2023

AbstractThe chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess actual intake of nutrients and other compounds. Despite of this, accurate data on nutrient intake are key for investigating associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (–)-epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake, generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.
Social Rank Alters the Synchrony of Attribute Integration in Altruistic Decisions
Authors: Ni Yinmei , Li Jian 
Published: November 2023

AbstractSocial rank, which represents the hierarchical dominance structure in societies, forms the backdrop against which most social decisions are made. Effective social decision-making demands the flexible integration of multifaceted information, including the relative weights and timings of different attributes. However, there is limited understanding of the potential impact of attribute timing on social preferences and, crucially, whether attribute weights and timings are susceptible to the influence of social rank. Here, through a two-stage social decision task, we manipulated subjects’ social rank before they engaged in altruistic decisions. By interrogating behavioral data through the lens of the time-varying drift diffusion process, we found that the behavioral patterns are better explained by a model that considers both attribute timing and weight. Interestingly, varying social ranks only modulate attribute timings in the decision process, leaving attribute weights unaffected. Furthermore, we demonstrated that individuals with more prosocial tendencies exhibited higher sensitivities of attribute timing in response to the changes of social rank and these results were replicated in a separate and larger cohort of participants. Our results underscore the intricate interplay between social rank and social attribute integration and introduce a new dimension to the computational mechanisms that underlie social decision-making.Author SummarySocial rank characterizes the background where most social decisions take place, however, the cognitive and computational mechanisms underlying how social rank influences altruistic decisions remain elusive. Here, combining a two-stage social decision task and time-varying DDM, we reveal that social rank specifically modulates attribute timings in the decision process, leaving attribute weights unaffected. Our results underscore the intricate interplay between social rank and social attribute integration during social decision-making.
Phylogenomics and biogeography of the feather lice (Phthiraptera: Ischnocera) of parrots
Authors: Johnson Kevin P. , Doña Jorge 
Published: November 2023

AbstractAvian feather lice (Phthiraptera: Ischnocera) have undergone morphological diversification into ecomorphs based on the mechanism for escaping host preening defenses. Parrot lice are one prominent example of this phenomenon, with wing, body, or head louse ecomorphs occurring on various groups of parrots. Currently defined genera of parrot lice typically correspond to this ecomorphological variation. Here we explore the phylogenetic relationships among parrot feather lice by sequencing whole genomes and assembling a target set of 2,395 nuclear protein coding genes. Phylogenetic trees based on concatenated and coalescent analyses of these data reveal highly supported trees with strong agreement between methods of analysis. These trees reveal that parrot feather lice fall into two separate clades that form a grade with respect to theBrueelia-complex. All parrot louse genera sampled by more than one species were recovered as monophyletic. The evolutionary relationships among these lice showed evidence of strong biogeographic signal, which may also be related to the relationships among their hosts.
Hepatocyte-Targeted siTAZ Therapy Lowers Liver Fibrosis in NASH Diet-Fed Chimeric Mice with Hepatocyte-Humanized Livers
Authors: Wang Xiaobo , Moore Mary P. , Shi Hongxue , Miyata Yoshinari , Donnelly Sara K. , Radiloff Daniel R. , Tabas Ira 
Published: November 2023

AbstractNonalcoholic steatohepatitis (NASH) is emerging as the most common cause of liver disease. Although many studies in mouse NASH models have suggested therapies, translation to humans is poor, with no approved drugs for NASH. One explanation may lie in inherent differences between mouse and human hepatocytes. We used NASH diet-fed chimeric mice reconstituted with human hepatocytes (hu-liver mice) to test a mechanism-based hepatocyte-targeted siRNA, GalNAc-siTaz, shown previously to block the progression to fibrotic NASH in mice. Mice were reconstituted with human hepatocytes following ablation of endogenous hepatocytes, resulting in ~95% human hepatocyte reconstitution. The mice were then fed a high-fat choline-deficient Lamino acid-defined diet for 6 weeks to induce NASH, followed by six weekly injections of GalNAc-siTAZ to silence hepatocyte-TAZ or control GalNAc-siRNA (GalNAc-control) while still on the NASH diet. The results revealed that GalNAc-siTAZ lowered human hepatic TAZ and IHH, the major TAZ target that promotes liver fibrosis in NASH. Most importantly, GalNAc-siTAZ decreased liver inflammation, hepatocellular injury, hepatic fibrosis, and profibrogenic mediator expression, and profibroticNOTCHvs. GalNAc-control, indicating that GalNAc-siTAZ decreased the progression of NASH in mice reconstituted with human hepatocytes. In conclusion, silencing TAZ in human hepatocytes suppresses liver fibrosis in a hu-liver model of NASH.Impact and ImplicationsNo drugs have yet been approved for NASH, which is a leading cause of liver disease worldwide. The findings here provide support for this therapeutic strategy of using hepatocyte-targeted siTAZ to decrease NASH progression. More generally, the study illustrates how hu-liver NASH mice can be used to evaluate therapeutic hepatocyte-targeted siRNAs to help prioritize future testing in human NASH.
Age-induced midbrain-striatum assembloids model early phenotypes of Parkinson’s disease
Authors: Barmpa Kyriaki , Saraiva Claudia , Gomez-Giro Gemma , Gabassi Elisa , Spitz Sarah , Brandauer Konstanze , Rodriguez Gatica Juan E. , Antony Paul , Robertson Graham , Papastefanaki Florentia , Kubitscheck Ulrich , Salti Ahmad , Ertl Peter , Matsas Rebecca , Edenhofer Frank , Schwamborn Jens C. 
Published: November 2023

AbstractParkinson’s disease (PD), one of the most common aging-associated neurodegenerative disorders, is characterised by nigrostriatal pathway dysfunction, caused by the gradual loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) of the midbrain and the dopamine depletion in the striatum. State of the art, humanin vitromodels are enabling the study of the dopaminergic neurons’ loss, but not the dysregulation of the dopaminergic network in the nigrostriatal pathway. Additionally, these models do not incorporate aging characteristics which potentially contribute to the development of PD. Therefore, it is conceivable that research conducted using these models overlooked numerous processes that contribute to disease’s phenotypes. Here we present a nigrostriatal pathway model based on midbrain-striatum assembloids with inducible aging. We show that these assembloids are capable of developing characteristics of the nigrostriatal connectivity, with catecholamine release from the midbrain to striatum and synapse formation between midbrain and striatal neurons. Moreover, Progerin-overexpressing assembloids acquire aging traits that lead to early phenotypes of PD. This new model shall help to reveal the contribution of aging as well as nigrostriatal connectivity to the onset and progression of PD.
Inhibition of epigenetic and cell cycle-related targets in glioblastoma cell lines: onametostat reduces proliferation and viability in both normoxic and hypoxic conditions
Authors: Lavogina Darja , Krõlov Mattias Kaspar , Vellama Hans , Modhukur Vijayachitra , Di Nisio Valentina , Lust Helen , Eskla Kattri-Liis , Salumets Andres , Jaal Jana 
Published: November 2023

AbstractThe choice of targeted therapies for treatment of glioblastoma patients is currently limited, and most glioblastoma patients die from the disease recurrence. Thus, systematic studies in simplified model systems are required to pinpoint the choice of targets for further exploration in clinical settings. Here, we report screening of 5 compounds targeting epigenetic writers or erasers and 6 compounds targeting cell cycle-regulating protein kinases against 3 glioblastoma cell lines following incubation under normoxic or hypoxic conditions. The viability assay indicated that PRMT5 inhibitor onametostat was endowed with high potency under both normoxic and hypoxic conditions in both MGMT-positive and MGMT-negative cell lines. In U-251 MG and U-87 MG cells, onametostat also affected the spheroid formation at concentrations lower than the currently used chemotherapeutic drug lomustine. Furthermore, in T98-G cell line, treatment with onametostat led to dramatic changes in the transcriptome profile by inducing the cell cycle arrest, suppressing RNA splicing, and down-regulating several major glioblastoma cell survival pathways. In this way, we confirmed that inhibition of epigenetic targets might represent a viable strategy for glioblastoma treatment even in the case of decreased chemo- and radiation sensitivity, although further studies in clinically more relevant models are required.
A Comprehensive Targeted Panel of 295 Genes: Unveiling Key Disease Initiating and Transformative Biomarkers in Multiple Myeloma
Authors: Ruhela Vivek , Oberoi Rupin , Gupta Ritu , Gupta Anubha 
Published: November 2023

AbstractMultiple myeloma (MM) is a haematological cancer that evolves from the benign precursor stage termed monoclonal gammopathy of undetermined significance (MGUS). Understanding the pivotal biomarkers, genomic events, and gene interactions distinguishing MM from MGUS can significantly contribute to early detection and an improved understanding of MM’s pathogenesis. This study presents a curated, comprehensive, targeted sequencing panel focusing on 295 MM-relevant genes and employing clinically oriented NGS-targeted sequencing approaches. To identify these genes, an innovative AI-powered attention model, theBio-Inspired Graph Network Learning-based Gene-Gene Interaction(BIO-DGI) model, was devised for identifyingDisease-InitiatingandDisease-Transformativegenes using the genomic profiles of MM and MGUS samples. The BIO-DGI model leverages gene interactions from nine protein-protein interaction (PPI) networks and analyzes the genomic features from 1154 MM and 61 MGUS samples. The proposed model outperformed base-line machine learning (ML) and deep learning (DL) models on quantitative performance metrics. Additionally, the BIO-DGI model identified the highest number of MM-relevant genes in the post-hoc analysis, demonstrating its superior qualitative performance. Pathway analysis highlighted the significance of top-ranked genes, emphasizing their role in MM-related pathways. Encompassing 9417 coding regions with a length of 2.630 Mb, the 295-gene panel exhibited superior performance, surpassing previously published panels in detecting genomic disease-initiating and disease-transformative events. The panel also revealed highly influential genes and their interactions within MM gene communities. Clinical relevance was confirmed through a two-fold univariate survival analysis, affirming the significance of the proposed gene panel in understanding disease progression. The study’s findings offer crucial insights into essential gene biomarkers and interactions, shaping our understanding of MM pathophysiology.
Withdrawn: Hypertension increases PPV for polycystic kidney disease inPKD1andPKD2variant carriers
Authors: Telis Natalie , McEwen Lisa , Bolze Alexandre , Judge Daniel P. , Pawloski Pamala A. , Grzymski Joseph J. , Hajek Catherine , Schiabor Barrett Kelly M. , Washington Nicole L. , Cirulli Elizabeth T. 
Published: November 2023

Withdrawal StatementThis version of the manuscript and associated files have been removed owing to concerns of data privacy.
The modified elevated gap interaction test: A novel paradigm to assess social preference
Authors: De Zeeuw Chris I. , Yu Si-yang , Chen Jiawei , van Hoogstraten Willem S. , van den Maagdenberg Arn M.J.M. , Bosman Laurens W.J. , Kros Lieke 
Published: November 2023

AbstractSocial deficits play a role in numerous psychiatric, neurological and neurodevelopmental disorders. Relating complex behavior, such as social interaction, to brain activity remains one of the biggest goals and challenges in neuroscience. Availability of standardized behavioral tests that assess social preference is however, limited. Here, we present a novel behavioral set-up and paradigm that we developed to measure social behavior, the modified elevated gap interaction test (MEGIT). In this test, animals are placed on one of two elevated platforms separated by a gap, in which they can engage in whisker-interaction with either a conspecific or an object. This allows quantification of social preference in real interaction rather than just proximity and forms an ideal setup for social behavior-related neuronal recordings. We provide a detailed description of the paradigm and its highly reliable, deep-learning based analysis, and show test results obtained from wild-type animals as well as genetic mouse models for disorders characterized by either hyposocial (autism spectrum disorder; ASD) or hypersocial (Williams Beuren syndrome; WBS) behavior. Wild-type animals show a clear preference for whisker interaction with another mouse rather than an inanimate object. This preference proved to be significantly smaller in mice carrying a mutation that can cause ASD in humans, whereas it is larger in WBS murine models. Differences in social preference became even more pronounced when corrected for hyperactive or repetitive behavior. The results indicate that MEGIT is a sensitive and reliable test for detecting and investigating social phenotypes.
Mechanical Resistance to Micro-Heart Tissue Contractility unveils early Structural and Functional Pathology in iPSC Models of Hypertrophic Cardiomyopathy
Authors: Guo Jingxuan , Jiang Huanzhu , Schuftan David , Moreno Jonathan D , Ramahdita Ghiska , Aryan Lavanya , Bhagavan Druv , Silva Jonathan , Huebsch Nathaniel 
Published: November 2023

AbstractHypertrophic cardiomyopathy is the most common cause of sudden death in the young. Because the disease exhibits variable penetrance, there are likely nongenetic factors that contribute to the manifestation of the disease phenotype. Clinically, hypertension is a major cause of morbidity and mortality in patients with HCM, suggesting a potential synergistic role for the sarcomeric mutations associated with HCM and mechanical stress on the heart. We developed anin vitrophysiological model to investigate how the afterload that the heart muscle works against during contraction acts together with HCM-linked MYBPC3 mutations to trigger a disease phenotype. Micro-heart muscle arrays (μHM) were engineered from iPSC-derived cardiomyocytes bearing MYBPC3 loss-of-function mutations and challenged to contract against mechanical resistance with substrates stiffnesses ranging from the of embryonic hearts (0.4 kPa) up to the stiffness of fibrotic adult hearts (114 kPa). Whereas MYBPC3+/-iPSC-cardiomyocytes showed little signs of disease pathology in standard 2D culture, μHMs that included components of afterload revealed several hallmarks of HCM, including cellular hypertrophy, impaired contractile energetics, and maladaptive calcium handling. Remarkably, we discovered changes in troponin C and T localization in the MYBPC3+/-μHM that were entirely absent in 2D culture. Pharmacologic studies suggested that excessive Ca2+intake through membrane-embedded channels, rather than sarcoplasmic reticulum Ca2+ATPase (SERCA) dysfunction or Ca2+buffering at myofilaments underlie the observed electrophysiological abnormalities. These results illustrate the power of physiologically relevant engineered tissue models to study inherited disease mechanisms with iPSC technology.
LIFE: A Deep Learning Framework for Laboratory Data Imputation in Electronic Health Records
Authors: Heilbroner Samuel P. , Carter Curtis , Vidmar David M. , Mueller Erik T. , Stumpe Martin C. , Miotto Riccardo 
Published: November 2023

AbstractLaboratory data in electronic health records (EHRs) is an effective source of information to characterize patient populations, inform accurate diagnostics and treatment decisions, and fuel research studies. However, despite their value, laboratory values are underutilized due to high levels of missingness. Existing imputation methods fall short, as they do not fully leverage patient clinical histories and are commonly not scalable to the large number of tests available in real-world data (RWD). To address these shortcomings, we present Laboratory Imputation Framework using EHRs (LIFE), a deep learning framework based on multi-head attention that is trained to impute any laboratory test value at any point in time in the patient’s journey using their complete EHRs. This architecture (1) eliminates the need to train a different model for each laboratory test by jointly modeling all laboratory data of interest; and (2) better clinically contextualizes the predictions by leveraging additional EHR variables, such as diagnosis, medications, and discrete laboratory results. We validate our framework using a large-scale, real-world dataset encompassing over 1 million oncology patients. Our results demonstrate that LIFE obtains superior or equivalent results compared to state-of-the-art baselines in 23 out of 25 evaluated laboratory tests and better enhances a downstream adverse event detection task in 7 out of 9 cases, showcasing its potential in efficiently estimating missing laboratory values and, consequently, in transforming the utilization of RWD in healthcare.