bluuebunny/crossref_metadata_2025_split huggingface dataset:
LAMC2 marks a tumor-initiating cell population with an aggressive signature in pancreatic cancer
Authors: Cave Donatella Delle , Buonaiuto Silvia , Mangini Maria , Sainz Bruno , Domenico Annalisa Di , Iavazzo Tea Teresa , Andolfi Gennaro , Duran Carme Cortina , Sevillano Marta , Heeschen Christopher , Colonna Vincenza , Corona Marco , Cucciardi Antonio , Guida Martina Di , Batlle Eduard , De Luca Annachiara , Lonardo Enza 
Published: March 2022

ABSTRACTTumor-initiating cells (TIC), also known as cancer stem cells, are considered a specific subpopulation of cells necessary for cancer initiation and metastasis. Here, we report a LAMC2-positive cell population, which is endowed with enhanced self-renewal capacity, and is sufficient for tumor initiation, differentiation, and driving metastasis. Mechanistically, mRNA profiling of these cells indicate a prominent squamous signature, and differentially activated pathways critical for tumor growth and metastasis, including deregulation of the TGF-β signaling pathway. Treatment with Vactosertib, a new small molecule inhibitor of transforming growth factor-β (TGF-β) type I receptor (activin receptor-like kinase-5, ALK5), completely abrogated the lung metastasis, primarily originating from LAMC2 expressing cells. Our results prompt further study of this TIC population in pancreatic cancer and exploration as a potential therapeutic target and/or biomarker.
Long-term temperature trend in Kamchatka supports expansion of harmful algae
Authors: Samarkhanov Kanat , Mirasbekov Yersultan , Meirkhanova Ayagoz , Zhumakhanova Adina , Malashenkov Dmitry , Kovaldji Alexander , Barteneva Natasha S. 
Published: March 2022

AbstractOcean coastal ecosystems are changing, and global shifts in temperature lead to the expansion and intensification of harmful algae. In conjunction with anthropogenic effects it may result in future exacerbation of harmful algal blooms. Here we use the 2002-2020 years record of surface ocean temperature data retrieved from Sentinel-2 satellite to examine the recent temperature trend in Avacha Bay, Kamchatka Peninsula. Satellite analysis demonstrated a temperature increase trend in ocean surface water during spring and summer months and detected algal bloom in July 2020 preceding a mass death of marine benthic life in September-October 2020. Using 16S rRNA and 18S rRNA gene amplicon nanopore-based sequencing, we analyzed microbial and microalgal communities in the water samples from area of 2020 algal blooms. Our results suggest the presence of potentially toxic and bloom-forming algae from genera related to former HABs (harmful algal blooms) in the Avacha Bay region. A better understanding of the potentially toxic algae phytoplankton composition in the shifting temperature environment and time-series monitoring of HABs is of utmost importance for scientific community. We suggest that satellite analysis in combination with eDNA monitoring by nanopore-based sequencing represents promising option to detect potentially toxic algae and follow bloom development.
Polymer nanoparticles pass the plant interface
Authors: Parkinson Sam J. , Tungsirisurp Sireethorn , Sikder Amrita , Lynch Iseult , O’Reilly Rachel K. , Napier Richard M 
Published: March 2022

AbstractAs agriculture strives to feed an ever-increasing number of people, it must adapt to cope with climate change. It is also clear that our biosphere is suffering from an increasing burden of anthropogenic waste which includes minute plastic particles. It is not yet known whether plants will accumulate such micro- and nanoplastic materials, nor how their surface properties might influence uptake. Therefore, we prepared well-defined block copolymer nanoparticles with a range of different sizes (Dh = 20 - 100 nm) and surface chemistries by aqueous dispersion polymerisation using different functional macro chain transfer agents. A BODIPY fluorophore was then incorporated via hydrazone formation and uptake of these fluorescent nanoparticles into intact roots and protoplasts of Arabidopsis thaliana was investigated using confocal microscopy. Where uptake was seen, it was inversely proportional to nanoparticle size. Positively charged particles accumulated around root surfaces and were not taken up by roots or protoplasts, whereas negatively charged nanoparticles accumulated slowly in protoplasts and roots, becoming prominent over time in the xylem of intact roots. Neutral nanoparticles exhibited early, rapid penetration into plant roots and protoplasts, but lower xylem loads relative to the negative nanoparticles. These behaviours differ from those recorded in animal cells and our results show that, despite robust cell walls, plants are vulnerable to nanoplastic particles in the water and soil. The data form both a platform for understanding plastic waste in the farmed environment, and may also be used constructively for the design of precision delivery systems for crop protection products.Significance StatementSustainable food production must keep pace with the growing global population, as well as adapt to climate change and other anthropogenic insults. It has become clear that micro-and nanoscale plastics are accumulating in all parts of the biosphere and we have set out to study how vulnerable plants are to such waste. We show that the size and surface properties of the designed plastics significantly affect both their speed of uptake and distribution within intact roots. Crucially, it is clear that rigid cell walls around plant cells are no barrier to the smallest particles and these pass into the plant’s vasculature. Our results relate to plastic waste but can also be used to develop precision vehicles for crop protection.
SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data
Authors: Kang Senbai , Borgsmüller Nico , Valecha Monica , Kuipers Jack , Alves Joao , Prado-López Sonia , Chantada Débora , Beerenwinkel Niko , Posada David , Szczurek Ewa 
Published: March 2022

AbstractSingle-cell DNA sequencing (scDNA-seq) has enabled the identification of single nucleotide somatic variants and the reconstruction of cell phylogenies. However, statistical phylogenetic models for cell phylogeny reconstruction from raw sequencing data are still in their infancy. Here we present SIEVE (SIngle-cell EVolution Explorer), a statistical method for the joint inference of somatic variants and cell phylogeny under the finite-sites assumption from scDNA-seq reads. SIEVE leverages raw read counts for all nucleotides at candidate variant sites, and corrects the acquisition bias of branch lengths. In our simulations, SIEVE outperforms other methods both in phylogenetic accuracy and variant calling accuracy. We apply SIEVE to three scDNA-seq datasets, for colorectal (CRC) and triple-negative breast cancer (TNBC), one of them generated by us. On simulated data, SIEVE reliably infers homo-and heterozygous somatic variants. The analysis of real data uncovers that double mutant genotypes are rare in CRC but unexpectedly frequent in TNBC samples.
Tracing immune cells around biomaterials with spatial anchors during large-scale wound regeneration
Authors: Yang Yang , Chu Chen-yu , Man Yi , Liu Li , Wang Chen-bing , Qu Yi-li 
Published: March 2022

AbstractInevitable skin scarring devoid of dermal appendages bring about unfavorable effects on both aesthetic and physiological functions. Here we offered an available method for large-area wound regeneration using biodegradable Aligned extracellular matrix (ECM) scaffold. Accelerating wound coverage and enhanced hair follicle (HF) neogenesis were observed with the implantation of biomaterials. Multimodal analysis during wound regeneration provides a unique lens through which we can explore the foreign body responses (FBR) around biomaterials. First, we identified cell heterogeneity in responses to ECM scaffolds using single-cell RNA sequencing. Next the spatial anchor highlighted preferential recruitment of T cells around biomaterials colocalized with hair follicle precursor cells. Reconstruction of signaling pathways suggested the pro-regenerative effect of the adaptive immune systems on HF neogenesis. Immunodeficient mice lacking mature T lymphocytes lost the ability to activate papillary fibroblast as well as stimulate HF regeneration, validating the potential therapeutic effect of the adaptive immune system activated by biomaterials. In conclusion, this study provided the further understanding of the FBR and facilitate the design of immunoregulatory biomaterials for biomedical application in the future.
Robust Estimation of 1/f Activity Improves Oscillatory Burst Detection
Authors: Seymour Robert A. , Alexander Nicholas , Maguire Eleanor A. 
Published: March 2022

AbstractNeural oscillations often occur as transient bursts with variable amplitude and frequency dynamics. Quantifying these effects is important for understanding brain-behaviour relationships, especially in continuous datasets. To robustly measure bursts, rhythmical periods of oscillatory activity must be separated from arrhythmical background 1/f activity, which is ubiquitous in electrophysiological recordings. The Better OSCillation (BOSC) framework achieves this by defining a power threshold above the estimated background 1/f activity, combined with a duration threshold. Here we introduce a modification to this approach called fBOSC which uses a spectral parametrisation tool to accurately model background 1/f activity in neural data. fBOSC (which is openly available as a MATLAB toolbox) is robust to power spectra with oscillatory peaks and can also model non-linear spectra. Through a series of simulations, we show that fBOSC more accurately models the 1/f power spectrum compared with existing methods. fBOSC was especially beneficial where power spectra contained a “knee” below ∼0.5-10 Hz, which is typical in neural data. We also found that, unlike other methods, fBOSC was unaffected by oscillatory peaks in the neural power spectrum. Moreover, by robustly modelling background 1/f activity, the sensitivity for detecting oscillatory bursts was standardised across frequencies (e.g. theta- and alpha-bands). Finally, using openly available resting state magnetoencephalography and intracranial electrophysiology datasets, we demonstrate the application of fBOSC for oscillatory burst detection in the theta-band. These simulations and empirical analyses highlight the value of fBOSC in detecting oscillatory bursts, including in datasets that are long and continuous with no distinct experimental trials.GRAPHICAL ABSRACTTo determine a power threshold for burst detection, the Better OSCillation framework (BOSC) estimates background 1/f activity by modelling neural power spectra. Here we introduce a modification, termed fBOSC, to more robustly estimate 1/f activity in situations with prominent oscillatory peaks and/or the presence of a non-linear “knee” in the power spectrum. This was shown to standardise burst detection across frequency bands in both simulated and empirical data.
Modeling phytoplankton-zooplankton interactions: opportunities for species richness and challenges for modern coexistence theory
Authors: Spaak Jurg W. , Adler Peter B. , Ellner Stephen P. 
Published: March 2022

AbstractMany potential mechanisms can sustain biodiversity, but we know little about their relative importance. To compare multiple mechanisms, we modeled a two-trophic planktonic food-web based on mechanistic species interactions and empirically measured species traits. We simulated thousands of communities under realistic and altered trait distributions to assess the relative importance of three potential drivers of species richness: resource competition, predator-prey interactions, and trait trade-offs. Next, we computed niche and fitness differences of competing zooplankton to obtain a deeper understanding of how these mechanisms limit species richness. We found that predator-prey interactions were the most important driver of species richness and that fitness differences were a better predictor of species richness than niche differences. However, for many communities we could not apply modern coexistence theory to compute niche and fitness differences due to complications arising from trophic interactions. We therefore need to expand modern coexistence theory to investigate multi-trophic communities.
Gfastats: conversion, evaluation and manipulation of genome sequences using assembly graphs
Authors: Formenti Giulio , Abueg Linelle , Brajuka Angelo , Brajuka Nadolina , Gallardo Cristo , Giani Alice , Fedrigo Olivier , Jarvis Erich D. 
Published: March 2022

AbstractMotivationWith the current pace at which reference genomes are being produced, the availability of tools that can reliably and efficiently generate genome assembly summary statistics has become critical. Additionally, with the emergence of new algorithms and data types, tools that can improve the quality of existing assemblies through automated and manual curation are required.ResultsWe sought to address both these needs by developing gfastats, as part of the Vertebrate Genomes Project (VGP) effort to generate high-quality reference genomes at scale. Gfastats is a standalone tool to compute assembly summary statistics and manipulate assembly sequences in fasta, fastq, or gfa [.gz] format. Gfastats stores assembly sequences internally in a gfa-like format. This feature allows gfastats to seamlessly convert fast* to and from gfa [.gz] files. Gfastats can also build an assembly graph that can in turn be used to manipulate the underlying sequences following instructions provided by the user, while simultaneously generating key metrics for the new sequences.Availability and implementationGfastats is implemented in C++. Precompiled releases (Linux, MacOS, Windows) and commented source code for gfastats are available under MIT license at https://github.com/vgl-hub/gfastats. Examples of how to run gfastats are provided in the Github. Gfastats is also available in Bioconda, in Galaxy (https://assembly.usegalaxy.eu) and as a MultiQC module [1] (https://github.com/ewels/MultiQC). An automated test workflow is available to ensure consistency of software updates.Supplementary informationSupplementary data are available at Bioinformatics online.
A survey to assess animal methods bias in scientific publishing
Authors: Krebs Catharine E. , Lam Ann , McCarthy Janine , Constantino Helder , Sullivan Kristie 
Published: March 2022

SummaryPublication of scientific findings is fundamental for research, pushing innovation and generating interventions that benefit society, but it is not without biases. Publication bias is generally recognized as journal’s preference for publishing studies based on the direction and magnitude of results. However, early evidence of a newly recognized type of publication bias has emerged in which journal policy, peer reviewers, or editors request that animal data be provided to validate studies produced using nonanimal-based approaches. We describe herein “animal methods bias” in publishing: a preference for animal-based methods where they may not be necessary or where nonanimal-based methods may be suitable, which affects the likelihood of a manuscript being accepted for publication. To gather evidence of animal methods bias, we set out to collect the experiences and perceptions of scientists and reviewers related to animal- and nonanimal-based experiments during peer review. We created a survey with 33 questions that was completed by 90 respondents working in various biological fields. Twenty-one survey respondents indicated that they have carried out animal-based experiments for the sole purpose of anticipating reviewer requests. Thirty-one survey respondents indicated that they have been asked by peer reviewers to add animal experimental data to their nonanimal study; 14 of these felt the request was sometimes justified, and 11 did not think it was justified. The data presented provide preliminary evidence of animal methods bias and indicate that status quo and conservatism biases may explain such attitudes by peer reviewers and editors.
BET inhibition sensitizes immunologically-cold Rb-deficient prostate cancer to immune checkpoint blockade
Authors: Olson Brian , Chaudagar Kiranj , Bao Riyue , Saha Sweta Sharma , Hong Christina , Rameshbabu Srikrishnan , Chen Raymond , Thomas Alison , Patnaik Akash 
Published: March 2022

ABSTRACTPurposeNon-T cell-inflamed immunologically “cold” tumor microenvironments (TME) are associated with poor responsiveness to immune checkpoint blockade (ICB), and can be sculpted by tumor cell genomics. Here we evaluated how Retinoblastoma (Rb) tumor suppressor loss of function (LOF), one of the most frequent alterations in human cancer and associated with lineage plasticity, poor prognosis and therapeutic outcomes, alters the TME, and whether therapeutic strategies targeting the molecular consequences of Rb loss enhance ICB efficacy.Experimental DesignWe performed bioinformatics analysis to elucidate the impact of endogenous Rb LOF on the immune TME in human primary and metastatic tumors. Next, we utilized isogenic murine models of Rb-deficient prostate cancer (PC) for in vitro and in vivo mechanistic studies to examine how Rb loss and bromodomain and extraterminal (BET) domain inhibition (BETi) reprograms the immune landscape, and evaluated in vivo therapeutic efficacy of BETi, singly and in combination with ICB and androgen deprivation therapy.ResultsRb loss was enriched in non-T cell-inflamed tumors, and Rb-deficient murine tumors demonstrated decreased immune infiltration in vivo. The BETi JQ1 increased immune infiltration into the TME through enhanced tumor cell STING/NF-κB activation and type I interferon (IFN) signaling within tumor cells, resulting in differential macrophage and T cell-mediated tumor growth inhibition and sensitization of Rb-deficient PC to ICB.ConclusionsBETi can reprogram the immunologically cold Rb-deficient TME via STING/NF-κB/IFN signaling to sensitize Rb-deficient PC to ICB. These data provide the mechanistic rationale to test combinations of BETi and ICB in clinical trials of Rb-deficient PC.STATEMENT OF TRANSLATIONAL RELEVANCERb LOF is one of the most common genomic alterations in human cancer, occurring in approximately 1/3 of advanced malignancies, Furthermore, loss of Rb correlates with enhanced aggressiveness and poor therapeutic outcomes. In this study, we demonstrate that loss of Rb is also associated with an immunosuppressive tumor microenvironment and lack of responsiveness to immune checkpoint blockade (ICB). As a strategy to overcome Rb LOF induced immunosuppression, we have demonstrated that BETi treatment drives STING/NF-κB signaling and type I interferon production within tumor cells, resulting in immune-mediated tumor control in Rb-deficient PC, which is accentuated by the combination with ICB and ADT. These findings provide a roadmap for maximizing the clinical translation of BET inhibitors into the clinic to treat aggressive-variant Rb-deficient PC.
Sub-cellular dynamic investigation of the multi-component drug on the gastric cancer cell BGC823 using Raman spectroscopy
Authors: Shang Wenhao , Fang Teng , Ye Anpei 
Published: March 2022

ABSTRACTThe potential of Raman spectroscopy in anticancer drug study has been demonstrated, yet its ability to character systematic cellular changes caused by multi-component drugs has not been explored. Here we used micro-Raman spectroscopy combined with bright field imaging to study Compound Kushen injection (CKI) at a sub-cellular level including intracellular vesicles(IVs). In our report, CKI caused dysfunction of DNA replication and repair was displayed by Raman spectrum (RS) from the cell nucleus. Meanwhile, the dynamics of CKI induced intracellular vesicles and cell component deconstruction was delineated by RS from the cytoplasm and IVs. The lipids-related biomolecular changes were also presented by the cytoplasm RS: the lipids level in the cytoplasm first descended then uprising. In conclusion, this study validated the mechanism and displayed the dynamics of CKI in treating cancer cells. We proved the capability of subcellular micro-Raman spectroscopy for detecting systematic cellular changes and its application for multi-component drug evaluation.
Strategies for sampling pseudo-absences for species distribution models in complex mountainous terrain
Authors: Descombes Patrice , Chauvier Yohann , Brun Philipp , Righetti Damiano , Wüest Rafael O. , Karger Dirk N. , Zurell Damaris , Zimmermann Niklaus E. 
Published: March 2022

AbstractPredictions from species distribution models (SDMs) that rely on presence-only data are strongly influenced by how pseudo-absences are derived. However, which strategies to generate pseudo-absences give rise to faithful SDMs in complex mountainous terrain, and whether species-specific or generic strategies perform better remain open questions.Here, across 500 plant species, we investigated comprehensively how predictions of SDMs at a 93 m spatial resolution are influenced by pseudo-absence strategies, using the complex topography of the Swiss mountains as a model system. We used five generic (random, equal-stratified, proportional-stratified, target, density) and three species-specific (target specific, density specific and geographic specific) approaches to derive pseudo-absence data. We conducted performance tests for each of our eight strategies in combination with (a) spatial bias, generated within our occurrence dataset on sites with highest sampling density, to investigate how this common bias problem influences the performance of pseudo-absence sampling strategies, and (b) a new approach to reduce model extrapolation in environmental space by including background data from all environmental conditions of the study area. SDMs were evaluated against an independent and well-sampled dataset of true presences and absences.The random, the density (generic), and the geographic specific (species-specific) strategies consistently performed best, even in cases of strong spatial sampling bias in the occurrence data. Including a background of environmentally stratified pseudo-absences improved predictions of species distributions towards environmental extremes, and significantly reduced spatial extrapolations of model predictions in environmental space.Our results indicate that both generic and species-specific pseudo-absence strategies allow estimating robust SDMs and we provide clear recommendations which strategies to choose in complex terrain and when presence data are prone to high sampling bias. In datasets with strong sampling bias, most pseudo-absence strategies produce extrapolation problems and we additionally recommend environmentally stratified pseudo-absences in these cases. Overall, in species rich datasets the use of complex and computationally demanding, species-specific pseudo-absence strategies may not always be justified compared to simpler generic approaches.