bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic Evaluation of High-Throughput PBK Modelling Strategies for the Prediction of Intravenous and Oral Pharmacokinetics in Humans
Authors: Geci René , Gadaleta Domenico , de Lomana Marina García , Ortega-Vallbona Rita , Colombo Erika , Serrano-Candelas Eva , Paini Alicia , Kuepfer Lars , Schaller Stephan 
Published: March 2024

AbstractPhysiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing within vitroorin silicomethods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for Non-Animal Methods. To address this limitation, High-throughput PBK modelling aims to rely exclusively onin vitroandin silicodata for model generation. Here, we evaluate a variety ofin silicotools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000+ publicly available humanin vivoconcentration-time profiles of 200+ compounds (IV and oral administration), as well asin silico,in vitroandin vivodetermined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collectedin vivoconcentration-time profiles. Our results show that even simple, generic High-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within 10-fold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for High-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of High-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.
Allograft and Autograft Anterior Cruciate Ligament Reconstructions Exhibit a Similar Biological Response to Cyclic Loading
Authors: Paschall Lauren , Tsai Ariane , Tabdanov Erdem , Dhawan Aman , Szczesny Spencer 
Published: March 2024

AbstractObjectiveAnterior cruciate ligament (ACL) reconstruction is one of the most commonly performed orthopaedic procedures. While outcomes are similar in the general patient population, the rerupture rate of non-irradiated allografts are 3-4 times higher than autografts in young active individuals. Previous studies suggest that the difference in clinical performance between graft types is due to impaired remodeling in allografts in response to loading. The objective of this study was to compare the remodeling response of autografts and allografts to cyclic loading. Furthermore, given that allografts are a foreign object and that immune cell signaling affects fibroblast mechanobiology, we compared markers of the immune cell composition between graft types.MethodsACL reconstructions were performed on New Zealand white rabbits, harvested 8 weeks post-surgery, and cyclically loaded to 2 MPa in a tensile bioreactor. Expression of markers for anabolic and catabolic tissue remodeling, as well as inflammatory cytokines and immune cells, were quantified using quantitative reverse transcription polymerase chain reaction.ResultsWe found that the expression of markers for tissue remodeling were not different between allografts and autografts. Similarly, we found that the expression of markers for immune cells were not different between allografts and autografts.ConclusionsThese data suggest that the poor clinical outcomes and impaired remodeling of allograft reconstructions compared to autografts is not due to a difference in graft mechanobiology.
Human airway macrophages are metabolically reprogrammed by IFN-γ resulting in glycolysis dependent functional plasticity
Authors: Cox Donal J , Connolly Sarah A , Maoldomhnaigh Cilian Ó , Brugman Aenea AI , Thomas Olivia Sandby , Duffin Emily , Gogan Karl M , Gallchobhair Oisin Ó , Murphy Dearbhla M , O’Rourke Sinead A , O’Connell Finbarr , Nadarajan Parthiban , Phelan James J , Gleeson Laura E , Basdeo Sharee A , Keane Joseph 
Published: March 2024

AbstractAirway macrophages (AM) are the predominant immune cell in the lung and play a crucial role in preventing infection, making them a target for host directed therapy. Macrophage effector functions are associated with cellular metabolism. A knowledge gap remains in understanding metabolic reprogramming and functional plasticity of distinct human macrophage subpopulations, especially in lung resident AM. We examined tissue-resident AM and monocyte derived macrophages (MDM; as a model of blood derived macrophages) in their resting state and after priming with IFN-γ or IL-4 to model the Th1/Th2 axis in the lung. Human macrophages, regardless of origin, had a strong induction of glycolysis in response to IFN-γ or upon stimulation. IFN-γ significantly enhanced cellular energetics in both AM and MDM by upregulating both glycolysis and oxidative phosphorylation. Upon stimulation, AM do not decrease oxidative phosphorylation unlike MDM which shift to “Warburg”-like metabolism. IFN-γ priming promoted cytokine secretion in AM. Blocking glycolysis with 2-deoxyglucose significantly reduced IFN-γ driven cytokine production in AM, indicating that IFN-γ induces functional plasticity in human AM, which is mechanistically mediated by glycolysis. Directly comparing responses between macrophages, AM were more responsive to IFN-γ priming and dependent on glycolysis for cytokine secretion than MDM. Interestingly, TNF production was under the control of glycolysis in AM and not in MDM. MDM exhibited glycolysis-dependent upregulation of HLA-DR and CD40, whereas IFN-γ upregulated HLA-DR and CD40 on AM independently of glycolysis. These data indicate that human AM are functionally plastic and respond to IFN-γ in a manner distinct from MDM. These data provide evidence that human AM are a tractable target for inhalable immunomodulatory therapies for respiratory diseases.
Phylotranscriptomics provides a treasure trove of flood tolerance mechanisms in the Cardamineae tribe
Authors: van Veen Hans , Müller Jana T. , Bartylla Malte M. , Akman Melis , Sasidharan Rashmi , Mustroph Angelika 
Published: March 2024

AbstractFlooding events are highly detrimental to most terrestrial plant species. However, there is an impressive diversity of plant species that thrive in flood-prone regions and represent a treasure trove of unexplored flood-resilience mechanisms. Here we surveyed a panel of four species from the Cardamineae tribe representing a broad tolerance range. This included the flood-tolerantCardamine pratensis,Rorippa sylvestrisandRorippa palustrisand the flood-sensitive speciesCardamine hirsuta. All four species displayed a quiescent strategy, evidenced by the repression of shoot growth underwater.Comparative transcriptomics analyses between the four species and the sensitive model speciesArabidopsis thalianawere facilitated viade-novotranscriptome assembly and identification of 16,902 universal orthogroups at a high resolution. Our results suggest that tolerance likely evolved separately in theCardamineandRorippaspecies. While theRoripparesponse was marked by a strong downregulation of cell-cycle genes,Cardamineminimized overall transcriptional regulation. However, a weak starvation signature was a universal trait of tolerant species, potentially achieved in multiple ways. It could result from a strong decline in cell-cycle activity, but is also intertwined with autophagy, senescence, day-time photosynthesis and night-time fermentation capacity. Our dataset provides a rich source to study adaptational mechanisms of flooding tolerance.
Blue appendages and temperature acclimation increase survival during acute heat stress in the upside-down jellyfish,Cassiopea xamachana
Authors: Maloney Megan E. , Buckley Katherine M. , Strader Marie E. 
Published: March 2024

AbstractUpside-down jellyfish (Cassiopea sp.) are highly tolerant to multiple abiotic stressors, including fluctuating temperatures associated with shallow marine habitats. This resilience may underlie the ability ofCassiopea sp.to inhabit a wide variety of tropical habitats across the globe. Additionally,Cassiopea sp.are marked by a conspicuous array of appendage coloration; individual medusae vary in the hue and number of oral appendages, which are often strikingly blue. The function of this coloration is not understood. We aimed to understand how extrinsic and intrinsic factors may shape thermal tolerance. AdultCassiopea xamachanawere collected from two sites that vary in daily temperature range within the Florida Keys and were subjected to acute lethal heat stress experiments. To quantify a whole-organism response to heat, we measured changes in bell pulsation, which likely plays a role in feeding, oxygen exchange, and symbiont uptake. Results show thatC. xamachanafrom the two collection sites do not exhibit different responses to heat, suggesting that temperature fluctuations do not prime individuals for higher thermal tolerance. Additionally,C. xamachanawith blue appendages survived significantly higher temperatures and exhibited less change in bell pulsation rates compared to non-blue individuals. Finally, color morphs were acclimated at either ambient (26 °C) or elevated (33 °C) temperatures. We found that acclimation at 33 °C, as well as appendage color in each treatment, led to higher survival under acute heat stress. Together, these findings highlight the importance of phenotypic plasticity and coloration inCassiopearesilience during heat stress.
G-quadruplex forming regions inGCKandTM6SF2are targets for differential DNA methylation in metabolic disease and hepatocellular carcinoma patients
Authors: Lahnsteiner Angelika , Ellmer Victoria , Oberlercher Anna , Liutkeviciute Zita , Schönauer Esther , Paulweber Bernhard , Aigner Elmar , Risch Angela 
Published: March 2024

AbstractThe alarming increase in global rates of metabolic diseases (MetDs) and their association with cancer risk renders them a considerable burden on our society. The interplay of environmental and genetic factors in causing MetDs may be reflected in DNA methylation patterns, particularly at non-canonical (non-B) DNA structures, such as G-quadruplexes (G4s) or R-loops. To gain insight into the mechanisms of MetD progression, we focused on DNA methylation and functional analyses on intragenic regions of two MetD risk genes, the glucokinase (GCK) exon 7 and the transmembrane 6 superfamily 2 (TM6SF2) intron 2-exon 3 boundary, which harbor non-B DNA motifs for G4s and R-loops.Pyrosequencing of 148 blood samples from a nested cohort study revealed significant differential methylation inGCKandTM6SF2in MetD patients versus healthy controls. Furthermore, these regions harbor hypervariable and differentially methylated CpGs also in hepatocellular carcinoma versus normal tissue samples from The Cancer Genome Atlas (TCGA). Permanganate/S1 nuclease footprinting with direct adapter ligation (PDAL-Seq), native polyacrylamide DNA gel electrophoresis and circular dichroism (CD) spectroscopy revealed the formation of G4 structures in these regions and demonstrated that their topology and stability is affected by DNA methylation. Detailed analyses including histone marks, chromatin conformation capture data, and luciferase reporter assays, highlighted the cell-type specific regulatory function of the target regions. Based on our analyses, we hypothesize that changes in DNA methylation lead to topological changes, especially inGCKexon 7, and cause the activation of alternative regulatory elements or potentially play a role in alternative splicing.Our analyses provide a new view on the mechanisms underlying the progression of MetDs and their link to hepatocellular carcinomas, unveiling non-B DNA structures as important key players already in early disease stages.
Automatic extraction of meaning from visual number symbols detected by frequency-tagged EEG in children
Authors: Rinsveld Amandine Van , Schiltz Christine 
Published: March 2024

AbstractSymbolic number representation and manipulation is key for successful mathematical learning. However, the mechanism by which at some point in development number symbols (i.e.,1,2,3, etc.) begin to automatically elicit useful meaning remains unresolved. Previous evidence highlighted that it is not possible to ignore the numerical magnitude when looking at number symbols, at least for adults. However, the neural mechanism behind the progressive automatization of symbol processing remains largely unknown, namely because these kinds of cognitive processes are difficult to isolate due to the general cognitive skills involved in any explicit task design. We thus developed an experimental paradigm specifically targeting the neural correlates of implicit magnitude representations by frequency-tagging magnitude changes within a visual stream of digits. Automatic magnitude processing was assessed by presenting a stream of number symbols with a frequency-tagged change of magnitude allowing to identify automatic categorization of the symbols by their magnitude in (pre)school-aged children. Stimuli were displayed with a sinusoidal contrast modulation at the frequency of 10 Hz and Steady-State Visual Evoked Potentials were recorded. These electrophysiological measurements showed a neural synchronization at the harmonics of the frequency of the magnitude changes recorded on electrodes encompassing bilateral occipitoparietal regions. The current findings indicate that magnitude is a salient semantic feature of the number symbols, which is deeply associated to digits in long-term memory across development.Significance StatementAcquiring strong semantic representations of numbers is crucial for future math achievement. However, the learning stage where magnitude information becomes automatically elicited by number symbols (i.e., Arabic digits from 1 to 9) remains unknown, namely due to the difficulty to measure unintentional automatic processing of magnitudes. We used a new experimental paradigm especially targeting the neural mechanisms involved in the automatic processing of magnitude information conveyed by number symbols. Frequency-tagged electrophysiological responses have the advantage to provide large amounts of reliable data with a high signal-to-noise ratio in a minimal amount of time. The current study is the first to take advantage of this in developmental populations to understand early automatic magnitude representations in children’s numeracy development. The electrophysiological responses demonstrate that the magnitude information is already automatically accessed from number symbols in children at the end of preschool, highlighting the importance of the first years of life for building automatized magnitude processing skills.
Prevalence of Undiagnosed Hypertension Among Adult Displaced Individuals in Baidoa Camps, Somalia
Authors: Jayte Mohamed 
Published: March 2024

AbstractIntroductionHypertension may be prevalent among internally displaced people who typically do not engage in sedentary activities throughout the day. However, the prevalence of hypertension in this population remains poorly understood. In this study, we aimed to determine the prevalence of undiagnosed hypertension and associated factors among adults living in internally displaced people (IDP) camps around Baidoa.MethodsA cross-sectional study was conducted, recruiting displaced persons in camps aged 18 years or older without a prior diagnosis of hypertension or current use of anti-hypertensive therapy. A standardized questionnaire was administered, and body mass index (BMI) was calculated. Hypertension was defined as two consistent measurements of systolic blood pressure ≥140mmHg and/or diastolic blood pressure ≥90mmHg, taken 4 hours apart. Multivariable logistic regression analysis was performed to identify factors independently associated with undiagnosed hypertension. Statistical significance was set at p<0.05.ResultsA total of 240 participants were enrolled, with a mean age of 39.4 ± 12.8 years. The majority were female (83.3%, n=199) and urban dwellers (88.3%, n=212). The prevalence of undiagnosed hypertension was 16.7% (n=40). Of the participants with hypertension, 40% (n=16) were younger than 40 years. Factors associated with undiagnosed hypertension included age >50 years (adjusted odds ratio (aOR): 7.0, 95% confidence interval (CI): 1.9 to 25.6, p=0.003), male gender (aOR: 4.2, 95% CI: 1.5 to 11.1, p=0.005), tobacco consumption (aOR: 2.6, 95% CI: 1.1 to 6.0, p=0.021), and being overweight (aOR: 3.6, 95% CI: 1.5 to 8.8, p=0.005).ConclusionApproximately one in six adult IDPs living in camps around Baidoa had undiagnosed hypertension, with a disproportionately high burden among those younger than 40 years. Further larger multi-centric studies are warranted to validate these findings.
MOTL: enhancing multi-omics matrix factorization with transfer learning
Authors: Hirst David , Térézol Morgane , Cantini Laura , Villoutreix Paul , Vignes Matthieu , Baudot Anaïs 
Published: March 2024

AbstractJoint matrix factorization is a popular method for extracting lower dimensional representations of multi-omics data. It disentangles underlying mixtures of biological signals, facilitating efficient sample clustering, disease subtyping, or biomarker identification, for instance. However, when a multi-omics dataset is generated from only a limited number of samples, the effectiveness of matrix factorization is reduced. Addressing this limitation, we introduce MOTL (Multi-Omics Transfer Learning), a novel framework for multi-omics matrix factorization with transfer learning based on MOFA (Multi-Omics Factor Analysis). MOTL infers latent factors for a small multi-omics dataset, with respect to those inferred from a large heterogeneous learning dataset. We designed two protocols to evaluate transfer learning approaches, based on simulated and real multi-omics data. Using these protocols, we observed that MOTL improves the factorization of multi-omics datasets, comprised of a limited number of samples, when compared to factorization without transfer learning. We showcase the usefulness of MOTL on a glioblastoma dataset comprised of a small number of samples, revealing an enhanced delineation of cancer status and subtype thanks to transfer learning.
Immune-oncology-microbiome axis may result in AKP or anti-AKP effects in intratumor microbiomes
Authors: Ma Zhanshan (Sam) 
Published: March 2024

AbstractAn emerging consensus regarding the triangle relationship between tumor, immune cells, and microbiomes is the immune-oncology-microbiome (IOM) axis, which stipulates that microbiomes can act as a discrete enabling (or disabling) characteristic that broadly influence the acquisition of certain hallmarks of cancer,i.e., a set of functional capabilities acquired by human cells during carcinogenesis and progression to malignant tumors. Specifically, it has been postulated that polymorphic microbiomes can either induce or inhibit some of the hallmark capacities (particularly, immune evasions) via their intersecting with two other enabling characteristics (genome instability and mutation, and tumor promoting inflammation). The net effects of the microbiomes can be either protective or deleterious effects on cancer development, malignant progression, and therapy responses. Nevertheless, there is not yet a mechanistic interpretation for IOM, especially regarding intratumoral microbiomes. Here, we propose to interpret the observed relationships, in which microbiomes can be complicit, bystanders, or in rare cases, oncomicrobes or foes, to either cancer cells or immune cells, possibly depend on specific microbial taxon, with the AKP (Anna Karenina principle)—that all heathy tissue microbiomes should be similar, and tumor microbiomes should be dissimilar with each other, in analogy with Leo Tolstoy’s aphorism that “all happy families look alike; each unhappy family is unhappy in its own way”. Given potentially double-sword nature of microbes, both AKP and anti-AKP should exist in the IOM axis. We test the AKP with microbiome datasets of 20+ cancer types from the TCGA database and find that the ratio of AKP/anti-AKP is about 3:1.Key PointsWe propose to interpret the observed relationships, in which microbiomes can be complicit, bystanders, or in rare cases, oncomicrobes or foes, to either cancer cells or immune cells, possibly depend on specific microbial taxon, with the AKP (Anna Karenina principle).We postulate that all heathy tissue microbiomes should be similar, and tumor microbiomes should be dissimilar with each other, in analogy with Leo Tolstoy’s aphorism that “all happy families look alike; each unhappy family is unhappy in its own way”.We test the AKP with microbiome datasets of 20+ cancer types from the TCGA database and find that the ratio of AKP/anti-AKP is about 3:1.
X-ray measurement of periarticular soft tissue predict readmission complications after Total Knee Arthroplasty
Authors: Hu Hanwen , Tao Ye , Qingyuan Zheng , Zhang Guoqiang , Ni Ming 
Published: March 2024

AbstractPurposeObesity is widely recognized as one of the risk factors for osteoarthritis. This study aims to explore the association between BMI and periarticular soft tissue on readmission complications in patients with previous joint replacement through the study of clinical and imaging data.MethodsThis retrospective study summarized 625 patients who underwent total knee arthroplasty. Imaging measurement data included several measurable soft tissue values and ratios on the anteroposterior. The association between BMI and imaging soft tissue measurement data with complications leading to readmission during follow-up was explored.ResultsAnalyzing 761 preoperative imaging measurements and postoperative follow-up data, a significant correlation (P<0.05) emerged between postoperative readmission complications and measured soft tissue thickness around the joint. A 1:4 paired test affirmed the independent predictive power (P<0.1) of select soft tissue data for readmission complications.ConclusionBMI proved insufficient in evaluating obesity-related complications post total knee arthroplasty. Preoperative imaging soft tissue data exhibited superior predictive capability for anticipating readmission complications after arthroplasty.Trial registration number: S2021-094-01Trial registration dates: 25/03/2021 Retrospectively registered