bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Imputation-Based Approach for Augmenting Sparse Epidemiological Signals
Authors: Benefield Amy E. , Williams Desiree , Nagraj VP 
Published: August 2024

AbstractNear-term disease forecasting and scenario projection efforts rely on the availability of data to train and evaluate model performance. In most cases, more extensive epidemiological time series data can lead to better modeling results and improved public health insights. Here we describe a procedure to augment an epidemiological time series. We used reported flu hospitalization data from FluSurv-NET and the National Healthcare Safety Network to estimate a complete time series of flu hospitalization counts dating back to 2009. The augmentation process includes concatenation, interpolation, extrapolation, and imputation steps, each designed to address specific data gaps. We demonstrate the forecasting performance gain when the extended time series is used to train flu hospitalization models at the state and national level.
First Report of Nipah virus shed in urine by fruit bats(Pteropus medius), Sri Lanka
Authors: Kohl Claudia , Siriwardana Sahan , Muzeniek Therese , Perera Thejanee , Bas Dilara , Öruc Mizgin , Brinkmann Annika , Becker-Ziaja Beate , Schwarz Franziska , Jeevatharan Hamsananthy , Weerasena Jagathpriya , Handunnetti Shiroma , Perera Inoka C. , Premawansa Gayani , Premawansa Sunil , Yapa Wipula , Nitsche Andreas 
Published: August 2024

AbstractNipah virus is an emerging pathogen with high public health relevance, causing outbreaks in South- and Southeast Asia with high case fatality rates. The natural reservoir host are fruit bats (Pteropus spp). In this study, we confirmed the presence of Nipah virus for the first time in Sri Lanka and are proving the genetic relatedness to Nipah virus strains from southern India, causing outbreaks in 2007, 2018, 2019 and 2023. It is noteworthy that the shedding of the Nipah Virus may have a temporal variation that correlates with the breeding season ofPteropus medius. Furthermore, preventive measures and possible mechanisms influencing viral shedding are discussed.
Variable prevalence of protectiveSpiroplasmainfection over time in two natural populations ofDrosophila hydei
Authors: Jones Jordan E. , Court Rebecca , Kageyama Daisuke , Obbard Darren J. , Hurst Gregory D. D. 
Published: August 2024

AbstractThe temporal dynamics of protective symbionts have rarely been characterized outside of aphid hosts. Here, we determine the prevalence ofSpiroplasmain two populations ofD. hydeiwhereSpiroplasmainfection had been previously recorded (UK and Japan). We observe that infection in both populations is variable over time and confirm the persistence ofSpiroplasmain the UK population for 9 years. Thus, variable prevalence over time appears to be a common feature of these symbioses.
Pulmonary129Xe Magnetic Resonance Gas-exchange Abnormalities in Moderate-Severe Asthma
Authors: Tcherner Sam , Mozaffaripour Ali , Matheson Alexander M , Biancaniello Alexander , Yamashita Cory , Parraga Grace 
Published: August 2024

ABSTRACTBACKGROUNDAsthma is recognized as an inflammatory disease of the airways, but inflammation may also affect the parenchyma and pulmonary vasculature. Hyperpolarized129Xe MRI and MR spectroscopy (MRS) provide a way to quantify the transfer of gas from the airways through the alveolar membrane and its binding to hemoglobin in the red blood cells (RBC) of the pulmonary microvasculature. The vast majority of129Xe MRS studies have investigated interstitial lung disease and the ratio of129Xe binding to the RBC and129Xe present in the alveolar membrane, (RBC:membrane) which is a surrogate of oxygen gas-transfer to the blood. We wondered if129Xe RBC:membrane would differ in asthma patients as compared to healthy volunteers because of recent work showing abnormally diminished pulmonary vascular small-vessel structure in severe-asthma.RESEARCH QUESTIONDo129Xe MRI gas-transfer measurements differ significantly in patients with moderate-severe asthma?STUDY DESIGN AND METHODSIn this retrospective study, healthy (NCT02484885) and asthma (NCT04651777;NCT02351141) participants were evaluated who provided written informed consent.RESULTSThirty-one participants with asthma (mean age=55 years ±18; 22 females) and 32 healthy volunteers (mean age=31 years ±14; 12 females) with129Xe MRS were evaluated. FEV1, VDP and DLCO/KCOwere significantly different in asthma compared to healthy participants. Age-corrected1RBC:membrane was significantly different in moderate-severe asthma (0.32±0.09) as compared to healthy participants (0.47±0.12,P=.01). RBC:membrane was significantly related to pulse-oximetry hemoglobin estimates (ρ=.29;P=.04) and DLCO(ρ=.71;P<.001). Significant relationships between129Xe RBC:membrane and age were observed in healthy (ρ=-.55;P=.002) and asthma participants (ρ=-0.49;P=.006), adjusted for sex. A significant ANCOVA model also revealed the influence of age (P=.002), sex (P<.001), hemoglobin (P=.003) and asthma status (P=.02) on RBC:membrane.INTERPRETATION129Xe RBC:membrane values were significantly different in moderate-severe asthma compared to healthy volunteers and were explained by age, sex, hemoglobin, and asthma status.
Substantial hierarchical reductions of genetic and morphological traits in the evolution of rotiferan parasites
Authors: Herlyn Holger , Hembrom Anju Angelina , Tosar Juan-Pablo , Mauer Katharina M. , Schmidt Hanno , Dezfuli Bahram Sayyaf , Hankeln Thomas , Bachmann Lutz , Sarkies Peter , Peterson Kevin J. , Fromm Bastian 
Published: August 2024

AbstractAbstract FigureGraphical abstractDuring the last 800 million years of evolution animals radiated into a vast range of diversity of species and disparity of forms and lifestyles. The process involved a near hierarchical increase in complexity from life forms with few cell types to organisms with many hundreds of cell-types. However, neither genome size nor number of protein-coding genes can explain these differences and their biological basis remains elusive. Yet, recent studies have suggested that the evolution of complexity is closely linked to the acquisition of a class of protein coding gene-regulators called microRNAs.In a regressive approach, to investigate the association between loss of organismal complexity and microRNAs, we here studied Syndermata, an invertebrate group including free-living rotifers (Monogononta, Bdelloidea), the epibiotic Seisonidea and the endoparasitic Acanthocephala. Genomic, transcriptomic and morphological characterization and comparisons across 25 syndermatan species revealed a strong correlation between loss of microRNAs, loss of protein-coding genes and decreasing morphological complexity. The near hierarchical loss extends to ∼85% loss of microRNAs and a ∼50% loss of BUSCO genes in the endoparasitic Acanthocephala, the most reduced group we studied.Together, the loss of ∼400 protein-coding genes and ∼10 metazoan core gene losses went along with one microRNA family loss. Furthermore, the loss of ∼4 microRNA families or ∼34 metazoan core genes associated with one lost morphological feature. These are the first quantitative insights into the regulatory impact of microRNAs on organismic complexity as a predictable consequence in regressive evolution of parasites.
Neural Representation Precision of Distance Predicts Arithmetic Performance
Authors: Zhao Hui , Qi Wang , Xu Jiahua , Yao Yaxin , Lv Jianing , Yang Jiaxin , Qin Shaozheng 
Published: August 2024

AbstractFocusing on the distance between magnitudes as the start point to investigate the mechanism of relationship detecting and its contribution to mathematical thinking, this study explores the precision of neural representations of numerical distance and their impact on arithmetic performance. By employing neural decoding techniques and representational similarity analysis, the present study investigates how accurately the brain represents numerical distances and how this precision relates to arithmetic skills. Thirty-two children participated, completing a dot number comparison task during fMRI scanning and an arithmetic fluency test. Results indicated that neural activation patterns in the intra-parietal sulcus decoded the distance between the presented pair of dots, and higher precision in neural distance representation correlates with better arithmetic performance. These findings suggest that the accuracy of neural decoding can serve as an index of the neural representation precision and that the ability to precisely encode numerical distances in the brain is a key factor in mathematical abilities. This provides new insights into the neural basis of mathematical cognition and learning.HighlightsUtilizing representational similarity analysis and neural decoding techniques, the research proposes that the accuracy of neural decoding serve as an index of neural representation precision.The precision of neural representation of numerical distances in the brain predicts task performance and math arithmetic proficiency in children.These findings imply the potential significance of relational information in general cognition and learning beyond mathematical learning.
Topological embedding and directional feature importance in ensemble classifiers for multi-class classification
Authors: Rocha Liedl Eloisa , Yassin Shabeer Mohamed , Kasapi Melpomeni , Posma Joram M. 
Published: August 2024

AbstractCancer is the second leading cause of disease-related death worldwide, and machine learning-based identification of novel biomarkers is crucial for improving early detection and treatment of various cancers. A key challenge in applying machine learning to high-dimensional data is deriving important features in an interpretable manner to provide meaningful insights into the underlying biological mechanismsWe developed a class-based directional feature importance (CLIFI) metric for decision tree methods and demonstrated its use for the The Cancer Genome Atlas proteomics data. We incorporated this metric into four algorithms, Random Forest (RF), LAtent VAriable Stochastic Ensemble of Trees (LAVASET), and Gradient Boosted Decision Trees (GBDTs), and a new extension incorporating the LAVA step into GBDTs (LAVABOOST). Both LAVA methods incorporate topological information from protein interactions into the decision function.The different models’ performance in classifying 28 cancers resulted in F1-scores of 93% (RF), 92% (LAVASET), 89% (LAVABOOST) and 86% (GBDT), with no method outperforming all others for individual cancer type prediction. The CLIFI metric allowed the visualisation of the model decision making functions, and the distributions indicated heterogeneity in several proteins (MYH11, ERα, BCL2) for different cancer types (including brain glioma, breast, kidney, thyroid and prostate cancer).We have developed an integrated, directional feature importance metric for multi-class decision tree-based classification models that facilitates interpretable feature importance assessment. The CLIFI metric can be used in conjunction with incorporating topological information into the decision functions of models to add inductive bias for improved interpretability.AvailabilityAll codes are available for data curation fromhttps://github.com/EloisaRL/TCGA-proteomics-pipelineand the LAVASET (v1.0) package fromhttps://github.com/melkasapi/LAVASET.
3D Reconstruction of Neuronal Allometry and Neuromuscular Projections in Asexual Planarians Using Expansion Tiling Light Sheet Microscopy
Authors: Lu Jing , Xu Hao , Wang Dongyue , Chen Yanlu , Inoue Takeshi , Gao Liang , Lei Kai 
Published: August 2024

AbstractThe intricate coordination of the neural network in planarian growth and regeneration has remained largely unrevealed, partly due to the challenges of imaging the central nervous system (CNS) in three dimensions (3D) with high resolution and within a reasonable timeframe. To address this gap in systematic imaging of the CNS in planarians, we adopted high-resolution, nanoscale imaging by combining tissue expansion and tiling light-sheet microscopy, achieving up to 4-fold linear expansion. Using an automatic 3D cell segmentation pipeline, we quantitatively profiled neurons and muscle fibers at the single-cell level in over 400 wild-type planarians during homeostasis and regeneration. We validated previous observations of neuronal cell number changes and muscle fiber distribution. We found that the increase in neuron cell number tends to lag behind the rapid expansion of somatic cells during the later phase of homeostasis. By imaging the planarian with up to 120 nm resolution, we also observed distinct muscle distribution patterns at the anterior and posterior poles. Furthermore, we investigated the effects ofβ-cateninRNAi on muscle fiber distribution at the posterior pole, consistent with changes in anterior-posterior polarity. The glial cells were observed to be close in contact with dorsal-ventral muscle fibers. Finally, we observed disruptions in neural-muscular networks ininr-1RNAi planarians. These findings provide insights into the detailed structure and potential functions of the neural-muscular system in planarians and highlight the accessibility of our imaging tool in unraveling the biological functions underlying their diverse phenotypes and behaviors.
Bovine H5N1 influenza virus binds poorly to human-type sialic acid receptors
Authors: Santos Jefferson J.S. , Wang Shengyang , McBride Ryan , Zhao Yan , Paulson James C. , Hensley Scott E. 
Published: August 2024

AbstractClade 2.3.4.4b highly pathogenic H5N1 avian influenza (HPAI) viruses started circulating widely in lactating dairy cattle in the United States at the end of 2023. Avian influenza viruses enter cells after binding to glycan receptors with terminally linked α2-3 sialic acid, whereas human influenza viruses typically bind to glycan receptors terminally linked α2-6 sialic acid in the upper respiratory tract. Here, we evaluated the receptor binding properties of hemagglutinin (HA) trimers from a clade 2.3.4.4b avian isolate (A/American Wigeon/South Carolina/22-000345-001/2021) and a cattle isolate (A/dairy cattle/Texas/24-008749-002-v/2024). Using two different methods, we found that both of the 2.3.4.4b H5s bound efficiently to glycan receptors with terminally linked α2-3 sialic acid with no detectable binding to glycan receptors with terminally linked α2-6 sialic acid. Our data suggest that clade 2.3.4.4b H5N1 viruses bind poorly to human receptors. It will be important to continue evaluating receptor binding properties of these viruses as they evolve in cattle.
Integrating Secondary Structure Information Enhances Phylogenetic Signal in Mitochondrial Protein Coding Genes
Authors: Cucini Claudio , Nardi Francesco , Pons Joan 
Published: August 2024

AbstractSecondary structures have long been held to carry significant phylogenetic information, but the difficulty in collating primary sequence and structural information has frequently hindered its full application in phylogenetic studies. Here, we focus on the implementation of secondary structure information (inner, outer and transmembrane regions) to improve partitioning in datasets of mitochondrial Protein-Coding Genes for phylogenetic analysis. A new pipeline called TRAMPO was developed to partition alignment sites accordingly. The inclusion of this structural information in phylogenetic analyses was shown to produce an improvement in the phylogenetic signal of mitochondrial protein coding genes. We speculate that the observed, distinctive, compositional bias towards thymines in second codon sites of transmembrane regions, as well as selection, may be among the possible driving forces. This effect is especially relevant in lineages older than 50 Ma, where the signal of second codon positions becomes more relevant as first and third codon sites begin experiencing saturation.
Mechanical Implications of Cellular Viscoelasticity, Cortex Polarity, Superelasticity, and Cell-Cell Junctions in Curved Tissues
Authors: Perez-Tirado Amaury , Unkelbach Ulla , Oswald Tabea A. , Rheinlaender Johannes , Schäffer Tilman E. , Mukenhirn Markus , Honigmann Alf , Janshoff Andreas 
Published: August 2024

ABSTRACTInvestigations of the response of curved epithelia derived from MDCK-II cells to external deformation involved indentation-relaxation experiments using colloidal probe microscopy. Notably, hemicysts exhibited lower tissue tension, greater compliance, and increased fluidity compared to cysts. The primary response to deformation turned out to be the in-plane expansion of the basal cortex/membrane of cells. Additionally, drug treatments applied to curved tissue, along with deformation of tailored mutants (such as E-cadherin knockout), revealed that tissue compliance over short time scales is influenced by an interplay of viscoelastic properties in individual cells, their apical-basal polarity, superelasticity of the shell, and excess interfacial area. Meanwhile, tissue resilience predominantly depends on the integrity of cell-cell contacts.
Normative Growth Modeling of Cortical Thickness Identify Neuroanatomical Variability and Distinct Subtypes in Brainstem Tumor Patients
Authors: Jia Heyuan , Wang Kaikai , Zhang Peng , Zhang Mingxin , Mai Yiying , Chu Congying , Yin Xuntao , Fan Lingzhong , Zhang Liwei 
Published: August 2024

AbstractBackgroundBrainstem tumors can cause structural brain changes, but the resulting heterogeneity within wholebrain structure is not well-studied. This study examines cortical thickness to identify patterns of structural alterations and explore underlying biological subtypes and their associations with clinical factors.Materials and MethodsThis study involved 124 pediatric brainstem tumor patients, aged 4-18 years. Cortical thickness was measured using CAT12 segmentation of 3D T1-weighted structural MRI. A normative model was established using data from 849 healthy children. Deviations in cortical thickness were estimated, and patients were classified into two subtypes using spectral clustering. Clinical statistical analyses were conducted with SPSS 26.0.ResultsThe normative model revealed significant heterogeneity in cortical thickness deviations, which correlated with tumor size and growth patterns. Focal tumors primarily caused negative deviations (t = 3.14, p = 0.02). There was a significant positive correlation between extreme positive deviations and tumor volume (r = 0.214, p = 0.010), and between extreme negative deviations and progression-free survival (r = 0.39, p = 0.008). Two subtypes were identified: Subtype 1, consisting of diffuse tumors with extreme positive deviations, and Subtype 2, consisting of focal tumors with extreme negative deviations. Subtype and tumor growth pattern significantly influenced duration (p < 0.01). The Kaplan-Meier survival curves for Subtype 1 and Subtype 2 demonstrated a significant difference in survival probabilities over time (p = 0.03).ConclusionOverall, this study identifies two major patterns of cortical thickness changes in brainstem tumor patients, enhancing our understanding of their relationship with cortical morphology. The findings suggest that cortical thickness alterations could serve as valuable biomarkers for predicting progression-free survival, which is crucial for clinical assessment and personalized treatment strategies. This research provides new insights into the physiological mechanisms by which brainstem tumors affect brain structure, supporting more precise clinical interventions and efficacy monitoring in the future.
Fertility Transition in India, 1985-2020: Selection of the Aggregation Function Matters
Authors: Chaurasia Aalok Ranjan 
Published: August 2024

AbstractThis paper analyses fertility transition in India during 1985-2020 based on the data from the official sample registration system. The analysis reveals that fertility transition in the country is contingent upon the way age-specific fertility rates are aggregated into a single composite indicator of fertility. When the simple arithmetic mean of age-specific fertility rates is used as a composite indicator of fertility, fertility in India has decreased almost linearly. However, when the geometric mean of age-specific fertility rates is used as the composite indicator of fertility, fertility transition in India appears to have stalled the period 2011-2013. The analysis also reveals that the change in marital fertility accounted for only about 35 per cent of the change in the simple arithmetic mean of age-specific fertility rates but more than half of the change in the geometric mean of age-specific fertility rates. The paper suggests that fertility transition should not be analysed in terms of the trend in the simple arithmetic mean of age-specific fertility rates or, equivalently, total fertility rate but should be analysed in terms of the trend in the geometric mean of age-specific fertility rates.
Perceptual super-resolution in multiple sclerosis MRI
Authors: Giraldo Diana L. , Khan Hamza , Pineda Gustavo , Liang Zhihua , Lozano Alfonso , Wijmeersch Bart Van , Woodruff Henry C. , Lambin Philippe , Romero Eduardo , Peeters Liesbet M. , Sijbers Jan 
Published: August 2024

AbstractMagnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a single-image super-resolution (SR) reconstruction framework that leverages SR convolutional neural networks (CNN) to enhance the through-plane resolution of structural MRI in people with MS (PwMS). Our strategy involves the supervised fine-tuning of CNN architectures, guided by a content loss function that promotes perceptual quality, as well as reconstruction accuracy, to recover high-level image features. Extensive evaluation with MRI data of PwMS shows that our SR strategy leads to more accurate MRI reconstructions than competing methods. Furthermore, it improves lesion segmentation on low-resolution MRI, approaching the performance achievable with high-resolution images. Results demonstrate the potential of our SR framework to facilitate the use of low-resolution retrospective MRI from real-world clinical settings to investigate quantitative image-based biomarkers of MS.
Optimization and performance analytics of global aircraft-based wastewater surveillance networks
Authors: St-Onge Guillaume , Davis Jessica T. , Hébert-Dufresne Laurent , Allard Antoine , Urbinati Alessandra , Scarpino Samuel V. , Chinazzi Matteo , Vespignani Alessandro 
Published: August 2024

AbstractAircraft wastewater surveillance has been proposed as a novel approach to monitor the global spread of pathogens. Here we develop a computational framework to provide actionable information for designing and estimating the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potentials and find that networks of 10 to 20 strategically placed wastewater sentinel sites can provide timely situational awareness and function effectively as an early warning system. The model identifies potential blind spots and suggests optimization strategies to increase WWSNs effectiveness while minimizing resource use. Our findings highlight that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSNs capabilities, stressing the importance of resource optimization. We show through retrospective analyses that WWSNs can significantly shorten the detection time for emerging pathogens. The presented approach offers a realistic analytic framework for the analysis of WWSNs at airports.