bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring
Authors: Widman Adam J. , Shah Minita , Øgaard Nadia , Khamnei Cole C. , Frydendahl Amanda , Deshpande Aditya , Arora Anushri , Zhang Mingxuan , Halmos Daniel , Bass Jake , Langanay Theophile , Rajagopalan Srinivas , Steinsnyder Zoe , Liao Will , Rasmussen Mads Heilskov , Jensen Sarah Østrup , Nors Jesper , Therkildsen Christina , Sotelo Jesus , Brand Ryan , Shah Ronak H. , Cheng Alexandre Pellan , Maher Colleen , Spain Lavinia , Krause Kate , Frederick Dennie T. , Malbari Murtaza S. , Marton Melissa , Manaa Dina , Winterkorn Lara , Callahan Margaret K. , Boland Genevieve , Wolchok Jedd D. , Saxena Ashish , Turajlic Samra , Imielinski Marcin , Berger Michael F. , Altorki Nasser K. , Postow Michael A. , Robine Nicolas , Andersen Claus Lindbjerg , Landau Dan A. 
Published: January 2022

ABSTRACTIn solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE uses deep learning and a ctDNA-specific feature space to increase SNV signal to noise enrichment in WGS by 300X compared to our previous noise suppression platform MRDetect. MRD-EDGE also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1Gb to 200Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal to noise enrichment in MRD-EDGE enablesde novomutation calling in melanoma without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition.
Predator-prey interactions in a warming world: the critical role of cold tolerance
Authors: Ge Xuezhen , Griswold Cortland K. , Newman Jonathan A. 
Published: January 2022

AbstractThermal tolerance mismatch within predator-prey systems may have pro-found effects on species population abundances and geographical distributions. To examine the generalized responses of a predator-prey system to climate change, we construct a biologically detailed stage-structured population dynamic model of interactions between ladybird beetles and aphids. We explore the model’s dynamics across the entire feasible parameter space of mean temperature and seasonality. Within this space, we explore different scenarios of predator and prey thermal tolerance mismatch to gain insight into how these thermal sensitivities affect the interacting species’ responses to climatic change. Our results indicate a predator’s cold tolerance has a larger effect on prey abundance than its heat tolerance. Mismatches between the predator’s and prey’s thermal tolerances also affect the species’ response to climate change. We identify three common patterns of species abundance across the feasible parameter space that relate to the type of thermal tolerance mismatches. Our study highlights the importance of understanding the complex interplay between climate change and species interactions.
A systematic evaluation of yeast sample preparation protocols for spectral identifications, proteome coverage and post-isolation modifications
Authors: den Ridder Maxime , Knibbe Ewout , van den Brandeler Wiebeke , Daran-Lapujade Pascale , Pabst Martin 
Published: January 2022

ABSTRACTThe importance of obtaining comprehensive and accurate information from cellular proteomics experiments asks for a systematic investigation of sample preparation protocols, particularly when working with unicellular organisms with strong cell walls, such as found in the model organism and cell factory S. cerevisiae. Sample preparation protocols may bias towards specific protein fractions or challenge the analysis of native protein modifications due to reagent-induced artefacts. Here, we performed a systematic comparison of sample preparation protocols using a matrix of different conditions commonly applied in whole cell lysate proteomics. The different protocols were evaluated for their overall fraction of identified spectra, proteome and amino acid sequence coverage, GO-term distribution and number of peptide modifications, by employing a combination of database and unrestricted modification search approaches. The best proteome and amino acid sequence coverage was achieved by using Urea combined with filter-aided or in-solution digestion protocols, where the overall outcomes were strongly influenced by the employed quenching procedure. Most importantly, the use of moderate incubation temperatures and times, circumvented excessive formation of modification artefacts. Extensive reagent-induced peptide modifications, however, were observed when using solvents such as acetone or additives such as formic acid. Moreover, several filter material-related modifications were observed when employing the filter-aided procedures. Ultimately, the best protocols enabled the identification of approximately 65–70% of all acquired fragmentation spectra, where additional de novo sequencing suggests that unidentified spectra were largely of too low spectral quality to provide confident spectrum matches. This study demonstrates the large impact of different sample preparation procedures on the proteomic analysis outcome, where the collected protocols and large sets of associated mass spectrometric raw data provide a resource to evaluate and design new protocols and guide the analysis of (native) peptide modifications in the model eukaryote yeast.
TGFβ receptor inhibition unleashes interferon-β production by tumor-associated macrophages and enhances radiotherapy efficacy
Authors: Hamon Pauline , de Thoré Marine Gerbé , Classe Marion , Signolle Nicolas , Liu Winchygn , Bawa Olivia , Meziani Lydia , Clémenson Céline , Milliat Fabien , Deutsch Eric , Mondini Michele 
Published: January 2022

ABSTRACTBackgroundTransforming growth factor-beta (TGFβ) can limit the efficacy of cancer treatments, including radiotherapy (RT), by inducing an immunosuppressive tumor environment. The association of TGFβ with impaired T cell infiltration and antitumor immunity is known, but the mechanisms by which TGFβ participates in immune cell exclusion and limits the efficacy of antitumor therapies warrant further investigations.MethodsWe used the clinically relevant TGFβ receptor 2 (TGFβR2)-neutralizing antibody MT1 and the small molecule TGFβR1 inhibitor LY3200882 and evaluated their efficacy in combination with RT against murine orthotopic models of head and neck and lung cancer.ResultsWe demonstrated that TGFβ pathway inhibition strongly increased the efficacy of RT. TGFβR2 antibody upregulated interferon beta (IFNβ) expression in tumor-associated macrophages (TAMs) within the irradiated tumors and favored T cell infiltration at the periphery and within the core of the tumor lesions. We highlighted that both the antitumor efficacy and inhibition of immune exclusion observed with the combination of MT1 and RT were dependent on type I interferon signaling.ConclusionsThese data shed new light on the role of TGFβ in limiting the efficacy of RT, identifying a novel mechanism involving the inhibition of macrophage-derived type I interferon production, and fostering the use of TGFβR inhibition in combination with RT in therapeutic strategies for the management of head and neck and lung cancer.
Alveolar cell fate selection and lifelong maintenance of AT2 cells by FGF signaling
Authors: Brownfield Douglas G. , de Arce Alex Diaz , Ghelfi Elisa , Gillich Astrid , Desai Tushar J. , Krasnow Mark A. 
Published: January 2022

SummaryThe lung’s gas exchange surface comprises thin alveolar type 1 (AT1) cells and cuboidal surfactant-secreting AT2 cells that are corrupted in some of the most common and deadly diseases including adenocarcinoma, emphysema, and SARS/Covid-19. These cells arise from an embryonic progenitor whose development into an AT1 or AT2 cell is thought to be dictated by differential mechanical forces. Here we show the critical determinant is FGF signaling. FGF Receptor 2 (Fgfr2) is expressed in mouse progenitors then restricts to nascent AT2 cells and remains on throughout life. Its ligands are expressed in surrounding mesenchyme and can, in the absence of differential mechanical cues, induce purified, uncommitted E16.5 progenitors to form alveolus-like structures with intermingled AT2 and AT1 cells. FGF signaling directly and cell autonomously specifies AT2 fate; progenitors lacking Fgfr2 in vitro and in vivo exclusively acquire AT1 fate. Fgfr2 loss in AT2 cells perinatally results in reprogramming to AT1 fate, whereas loss or inhibition later in life immediately triggers AT2 apoptosis followed by a compensatory regenerative response. We propose Fgfr2 signaling directly selects AT2 fate during development, induces a cell non-autonomous secondary signal for AT1 fate, and stays on throughout life to continuously maintain healthy AT2 cells.One Sentence SummaryFGF signaling induces and distinguishes the two cell types of the lung’s gas exchange surface, and the pathway remains on throughout life to maintain one that can be transformed into lung cancer or targeted in the deadly form of SARS/Covid-19.
Acclimation of phenology relieves leaf longevity constraints in deciduous forests
Authors: Marqués Laura , Hufkens Koen , Bigler Christof , Crowther Thomas W. , Zohner Constantin M. , Stocker Benjamin D. 
Published: January 2022

AbstractLeaf phenology is key for regulating total growing season mass and energy fluxes. Long-term temporal trends towards earlier leaf unfolding are observed across Northern Hemisphere forests. Phenological dates also vary between years, whereby end-of-season (EOS) dates correlate positively with start-of-season (SOS) dates and negatively with growing season total net CO2 assimilation (Anet). These associations have been interpreted as the effect of a constrained leaf longevity or of premature carbon (C) sink saturation - with far-reaching consequences for long-term phenology projections under climate change and rising CO2. Here, we use multi-decadal ground and remote-sensing observations to show that the relationships between Anet and EOS are opposite at the interannual and the decadal time scales. A decadal trend towards later EOS persists in parallel with a trend towards increasing Anet - in spite of the negative Anet-EOS relationship at the interannual scale. This indicates that acclimation of phenology has enabled plants to transcend a constrained leaf longevity or premature C sink saturation over the course of several decades, leading to a more effective use of available light and a sustained extension of the vegetation CO2 uptake season over time.
Structural changes after early life adversity in rodents: a systematic review with meta-analysis
Authors: Joëls Marian , Kraaijenvanger Eline , Sarabdjitsingh R. Angela , Bonapersona Valeria 
Published: January 2022

AbstractEarly life adversity (ELA) is a well-documented risk factor for psychiatric illnesses in humans. This risk may, in part, be conferred by structural changes induced by ELA, lasting into adulthood. We here review the evidence for such lasting structural changes in rodent models for ELA involving altered maternal care during the first two postnatal weeks. In total, we extracted data from 64 studies reporting on 260 comparisons in adult rats or mice which experienced ELA or control treatment. Most of the observations concerned structural changes in the hippocampus of adult male rats earlier exposed to maternal separation. A 3-level meta-analysis revealed that ELA reduced hippocampal volume and the number of dendritic branches as well as dendritic length of principal hippocampal cells. No differences were observed across the hippocampal subfields. In terms of adult neurogenesis in the dentate subgranular zone, both staining for BrdU and the early neuronal marker DCX were significantly reduced, while the general proliferation marker Ki67 remained unchanged. The neuronal growth factor BDNF did not show significant changes, although the unexplained heterogeneity was moderate. Generally, the effect of ELA compared to control on structural markers was not affected by additional stressors experienced in life. Overall, the data available support the notion that ELA, at least in the hippocampus of male rats, lastingly reduces volume, hampers dendritic growth and suppresses adult neurogenesis.
Serological screening suggests single SARS-CoV-2 spillover events to cattle
Authors: Wernike Kerstin , Böttcher Jens , Amelung Silke , Albrecht Kerstin , Gärtner Tanja , Donat Karsten , Beer Martin 
Published: January 2022

AbstractWidespread human SARS-CoV-2 infections pose a constant risk for virus transmission to animals. Here, we serologically investigated 1000 cattle samples collected in late 2021 in Germany. Eleven sera tested antibody-positive, indicating that cattle may be occasionally infected by contact to SARS-CoV-2-positive keepers, but there is no indication of further spreading.
Improvements in estimating bioaccumulation metrics in the light of toxicokinetic models and Bayesian inference
Authors: Ratier Aude , Lopes Christelle , Charles Sandrine 
Published: January 2022

AbstractThe surveillance of chemical substances in the scope of Environmental Risk Assessment (ERA) is classically performed through bio-assays from which data are collected and then analysed and/or modelled. Some analysis are based on the fitting of toxicokinetic (TK) models to assess the bioaccumulation capacity of chemical substances via the estimation of bioaccumulation metrics as required by regulatory documents. Given that bio-assays are particularly expensive and time consuming, it is of crucial importance to deeply benefit from all information contained in the data. By revisiting the calculation of bioaccumulation metrics under a Bayesian framework, this paper suggests changes in the way of characterising the bioaccumulation capacity of chemical substances. For this purpose, a meta-analysis of a data-rich TK database was performed, considering uncertainties around bioaccumulation metrics. Our results were statistically robust enough to suggest an additional criterion to the single median estimate of bioaccumulation metrics to assign a chemical substance to a given bioaccumulation capacity. Our proposal is to use the 75th percentile of the uncertainty interval of the bioaccumulation metrics, which revealed an appropriate complement for the classification of chemical substances (e.g., PBT (persistent, bioaccumulative and toxic) and vPvB (very persistent and very bioaccumulative) under the EU chemicals legislation). The 75% quantile proved its efficiency, similarly classifying 90% of the chemical substances as the conventional method.
Re-routing metabolism by the mitochondrial pyruvate carrier inhibitor MSDC-0160 attenuates neurodegeneration in a rat model of Parkinson’s disease
Authors: Mallet David , Goutaudier Raphael , Barbier Emmanuel L. , Carnicella Sebastien , Colca Jerry R. , Fauvelle Florence , Boulet Sabrina 
Published: January 2022

AbstractBackgroundA growing body of evidence supports the idea that mitochondrial dysfunction might represent a key feature of Parkinson’s disease (PD). Central regulators of energy production, mitochondria are also involved in several other essential functions such as cell death pathways and neuroinflammation which make them a potential therapeutic target for PD management. Interestingly, recent studies related to PD have reported a neuroprotective effect of targeting mitochondrial pyruvate carrier (MPC) by the insulin sensitizer MSDC-0160. As the sole point of entry of pyruvate into the mitochondrial matrix, MPC plays a crucial role in energetic metabolism which is impacted in PD. This study therefore aimed at providing insights into the mechanisms underlying the neuroprotective effect of MSDC-0160.MethodsWe investigated behavioral, cellular and metabolic impact of chronic MSDC-0160 treatment in unilateral 6-OHDA PD rats. We evaluated mitochondrial related processes through the expression of pivotal mitochondrial enzymes in dorsal striatal biopsies and the level of metabolites in serum samples using nuclear magnetic resonance spectroscopy (NMR)-based metabolomics.ResultsMSDC-0160 treatment in unilateral 6-OHDA rats improved motor behavior, decreased dopaminergic denervation and reduced mTOR activity and neuroinflammation. Concomitantly, MSDC-0160 administration strongly modified energy metabolism as revealed by increased ketogenesis, beta oxidation and glutamate oxidation to satisfy energy needs and maintain energy homeostasis.ConclusionMSDC-0160 exerts its neuroprotective effect through reorganization of multiple pathways connected to energy metabolism.
Symbolic Kinetic Models in Python (SKiMpy): Intuitive modeling of large-scale biological kinetic models
Authors: Weilandt Daniel R. , Salvy Pierre , Masid Maria , Fengos Georgios , Denhardt-Erikson Robin , Hosseini Zhaleh , Hatzimanikatis Vassily 
Published: January 2022

AbstractMotivationLarge-scale kinetic models are an invaluable tool to understand the dynamic and adaptive responses of biological systems. The development and application of these models have been limited by the availability of computational tools to build and analyze large-scale models efficiently. The toolbox presented here provides the means to implement, parametrize and analyze large-scale kinetic models intuitively and efficiently.ResultsWe present a Python package (SKiMpy) bridging this gap by implementing an efficient kinetic modeling toolbox for the semiautomatic generation and analysis of large-scale kinetic models for various biological domains such as signaling, gene expression, and metabolism. Furthermore, we demonstrate how this toolbox is used to parameterize kinetic models around a steady-state reference efficiently. Finally, we show how SKiMpy can imple-ment multispecies bioreactor simulations to assess biotechnological processes.AvailabilityThe software is available as a Python 3 package on GitHub:https://github.com/EPFL-LCSB/SKiMpy, along with adequate documentation.Contactvassily.hatzimanikatis@epfl.ch
CView: A network based tool for enhanced alignment visualization
Authors: Linheiro Raquel , Lobo Diana , Sabatino Stephen , Archer John 
Published: January 2022

AbstractTo date basic visualization of sequence alignments have largely focused on displaying per-site columns of nucleotide, or amino acid, residues along with associated frequency summarizations. The persistence of this tendency to the more recent tools designed for the viewing of mapped read data indicates that such a perspective not only provides a reliable visualization of per-site alterations, but also offers implicit reassurance to the end user in relation to data accessibility. However, the initial insight gained is limited, something that is especially true when viewing alignments consisting of many sequences representing differing factors, such as geographical location, date and subtype. A basic alignment viewer can have potential to increase initial insight through visual enhancement, whilst not delving into the realms of complex sequence analysis. Here we present CView, a visualizer that expands on the per-site representation of residues through the incorporation of a dynamic network that is based on the summarization of diversity present across different regions of the alignment. Within the network nodes are based on the clustering of sequence fragments spanning windows that are placed consecutively along the alignment. Edges are placed between nodes of neighbouring windows where they share sequence id’s. Thus, if a single node is selected on the network, then the relationship that all sequences passing through that node have to other regions of diversity within the alignment can be instantly observed through the tracing of paths. In addition to augmenting visual insight, CView provides many export features including variant summarization, per-site residue and kmer frequency matrixes, consensus sequence generation, alignment dissection as well as general sequence clustering, each of which are useful across a range of research areas. The software has been designed to be user friendly, intuitive and interactive. It, along with source code, a quick start guide and test data, are available through the SourceForge project page: https://sourceforge.net/projects/cview/.
Sensory system-specific associations between brain structure and balance
Authors: Hupfeld KE , McGregor HR , Hass CJ , Pasternak O , Seidler RD 
Published: January 2022

AbstractNearly 75% of older adults in the United States report balance problems. Balance difficulties are more pronounced during sensory feedback perturbation (e.g., standing with the eyes closed or on foam). Although it is known that aging results in widespread brain atrophy, less is known about how brain structure relates to balance performance under varied sensory conditions in older age. We measured postural sway of 36 young (18-34 years) and 22 older (66-84 years) adults during four conditions: eyes open, eyes closed, eyes open on foam, and eyes closed on foam. We calculated three summary measures indicating visual, proprioceptive, and vestibular contributions to balance. We also collectedT1-weighted and diffusion-weighted anatomical MRI scans. We aimed to: 1) test for age group differences in brain structure-balance relationships across a range of structural brain measures (i.e., volumetric, surface, and white matter microstructure); and 2) assess how brain structure measures relate to balance, regardless of age. Across both age groups, thinner cortex in multisensory integration regions was associated with greater reliance on visual inputs for balance. Greater gyrification within sensorimotor and parietal cortices was associated with greater reliance on proprioceptive inputs for balance. Poorer vestibular function was correlated with thinner vestibular cortex, greater gyrification within sensorimotor, parietal, and frontal cortices, and lower free water-corrected axial diffusivity in the superior-posterior corona radiata and across the corpus callosum. These results contribute to our scientific understanding of how individual differences in brain structure relate to balance. This has implications for developing brain stimulation interventions to improve balance.Significance StatementOlder age is associated with greater postural sway, particularly when sensory information is perturbed (e.g., by closing one’s eyes). Our work contributes to the field by identifying how individual differences in regional brain structure relate to balance under varying sensory conditions in young and older adults. Across both age groups, lower cortical thickness in sensory integration and vestibular regions, greater gyrification within sensorimotor, parietal, and temporal regions, and lower free water-corrected axial diffusivity in the corpus callosum and corona radiata were related to individual differences in balance scores. We identified brain structures that are associated with specific sensory balance scores; therefore, these results have implications for which brain regions to target in future interventions for different populations.