bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine-learning approach to human footprint index estimation with applications to sustainable development
Authors: Keys Patrick W. , Barnes Elizabeth A. , Carter Neil H. 
Published: September 2020

AbstractThe human footprint index is an extensively used tool for interpreting the accelerating pressure of humanity on Earth. Up to now, the process of creating the human footprint index has required significant data and modeling, and updated versions of the index often lag the present day by many years. Here we introduce a near-present, global-scale machine learning-based human footprint index (ml-HFI) which is capable of routine update using satellite imagery alone. We present the most up-to-date map of the human footprint index, and document changes in human pressure during the past 20 years (2000 to 2019). Moreover, we demonstrate its utility as a monitoring tool for the United Nations Sustainable Development Goal 15 (SDG15), “Life on Land”, which aims to foster sustainable development while conserving biodiversity. We identify 43 countries that are making progress toward SDG15 while also experiencing increases in their ml-HFI. We examine a subset of these in the context of conservation policies that may or may not enable continued progress toward SDG15. This has immediate policy relevance, since the majority of countries globally are not on track to achieve Goal 15 by the declared deadline of 2030. Moving forward, the ml-HFI may be used for ongoing monitoring and evaluation support toward the twin goals of fostering a thriving society and global Earth system.
Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers
Authors: Yao Jun , Xu Hengyi , Ferrick-Kiddie Elizabeth A. , Nottingham Ryan M. , Wu Douglas C. , Ares Manuel , Lambowitz Alan M. 
Published: September 2020

AbstractPrevious Thermostable Group II Intron Reverse Transcriptase sequencing (TGIRT-seq) found that human plasma contains short (≤300 nt) structured full-length excised linear intron RNAs (FLEXIs) with potential utility as blood-based biomarkers. Here, TGIRT-seq identified >9,000 different FLEXIs in human cells, including relatively abundant FLEXIs with cell-type-specific expression patterns. Analysis of published CLIP-seq datasets identified 126 RNA-binding proteins (RBPs) that bind different FLEXIs, including 53 RBPs that bind ≥30 FLEXIs. These RBPs included splicing factors, transcription factors, a chromatin remodeling protein, cellular growth regulators, and proteins with cytoplasmic functions. Analysis of published datasets identified subsets of these RBPs that bind at FLEXI splice sites and impact alternative splicing or FLEXI host gene mRNA levels. Hierarchical clustering identified 6 subsets of RBPs whose binding sites were co-enriched in different subsets of FLEXIs: AGO1-4 and DICER, including but not limited to annotated agotrons and mirtron pre-miRNAs; DKC1, NOLC1, SMNDC1, and AATF (Apoptosis Antagonizing Transcription Factor), including but not limited to FLEXIs encoding snoRNAs; two sets of alternative splicing factors; and two sets that included RBPs with cytoplasmic functions (e.g., LARP4, PABPC4, METAP2, and ZNF622) together with nuclear regulatory proteins. The subsets of host genes encoding FLEXIs that bind these RBPs were enriched with non-FLEXI other short and long introns that bind the same RBPs, and TGIRT-seq of nuclear and cytoplasmic fractions from 4 cell lines showed cytoplasmic enrichment of FLEXIs with binding sites for RBPs that function in the cytoplasm. Collectively, our findings suggest that different subsets of RBPs bind FLEXIs and other introns to coordinately regulate the expression of functionally related host genes and then co-localize with stably bound FLEXIs to different intracellular locations. The cell-type specific expression of relatively abundant FLEXIs suggests utility as cellular as well as blood-based RNA biomarkers.
Automated detection of Hainan gibbon calls for passive acoustic monitoring
Authors: Dufourq Emmanuel , Durbach Ian , Hansford James P. , Hoepfner Amanda , Ma Heidi , Bryant Jessica V. , Stender Christina S. , Li Wenyong , Liu Zhiwei , Chen Qing , Zhou Zhaoli , Turvey Samuel T. 
Published: September 2020

1AbstractExtracting species calls from passive acoustic recordings is a common preliminary step to ecological analysis. For many species, particularly those occupying noisy, acoustically variable habitats, the call extraction process continues to be largely manual, a time-consuming and increasingly unsustainable process. Deep neural networks have been shown to offer excellent performance across a range of acoustic classification applications, but are relatively underused in ecology.We describe the steps involved in developing an automated classifier for a passive acoustic monitoring project, using the identification of calls of the Hainan gibbon(Nomascus hainanus), one of the world’s rarest mammal species, as a case study. This includes preprocessing - selecting a temporal resolution, windowing and annotation; data augmentation; processing - choosing and fitting appropriate neural network models; and postprocessing - linking model predictions to replace, or more likely facilitate, manual labelling.Our best model converted acoustic recordings into spectrogram images on the mel frequency scale, using these to train a convolutional neural network. Model predictions were highly accurate, with per-second false positive and false negative rates of 1.5% and 22.3%. Nearly all false negatives were at the fringes of calls, adjacent to segments where the call was correctly identified, so that very few calls were missed altogether. A postprocessing step identifying intervals of repeated calling reduced an eight-hour recording to, on average, 22 minutes for manual processing, and did not miss any calling bouts over 72 hours of test recordings. Gibbon calling bouts were detected regularly in multi-month recordings from all selected survey points within Bawangling National Nature Reserve, Hainan.We demonstrate that passive acoustic monitoring incorporating an automated classifier represents an effective tool for remote detection of one of the world’s rarest and most threatened species. Our study highlights the viability of using neural networks to automate or greatly assist the manual labelling of data collected by passive acoustic monitoring projects. We emphasise that model development and implementation be informed and guided by ecological objectives, and increase accessibility of these tools with a series of notebooks that allow users to build and deploy their own acoustic classifiers.
Nicotine and Opioid Polysubstance Abuse: Enhancement of opioid self-administration by systemic nicotine and modulation of opioid-associated memories by insular nicotine
Authors: Loney Gregory C , King Christopher P , Meyer Paul J 
Published: September 2020

AbstractConcurrent nicotine use is associated with increased liability for the development and exacerbation of opioid-use disorders. Habitual use of nicotine containing products increases propensity to misuse prescription opioids and its prevalence is substantially increased in individuals currently involved in opioid-treatment programs. Nicotine enhances self-administration of many classes of drugs in rodents, though evidence for direct effects on opioids is lacking. We sought to measure the effects of nicotine pretreatment on the reinforcing efficacy of opioids in both self-administration and contextual conditioning paradigms. First, we measured the effect of systemic nicotine pretreatment on self-administration of two opioids. Additionally, we measured the degree to which systemic nicotine pretreatment impacts the formation of morphine-associated contextual memories in conditioned taste avoidance and place preference paradigms. Given the involvement of the insula in the maintenance of substance abuse, its importance in nicotine addiction, and findings that insular inactivation impairs contextual drug conditioning, we examined whether nicotine administered directly to the insula could recapitulate the effects of systemic nicotine. We demonstrate that systemic nicotine pretreatment significantly enhances opioid self-administration and alters contextual conditioning. Furthermore, intra-insula nicotine similarly altered morphine contextual conditioning by blocking the formation of taste avoidance at all three morphine doses tested (5.0, 10, & 20 mg/kg), while shifting the dose-response curve of morphine in the place preference paradigm rightward. In conclusion, these data demonstrate that nicotine facilitates opioid intake and is partly acting within the insular cortex to obfuscate aversive opiate memories while potentiating approach to morphine-associated stimuli at higher doses.
Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI
Authors: Raamana Pradeep Reddy , Theyers Athena , Selliah Tharushan , Bhati Piali , Arnott Stephen R. , Hassel Stefanie , Nanayakkara Nuwan D. , Scott Christopher J. M. , Harris Jacqueline , Zamyadi Mojdeh , Lam Raymond W. , Milev Roumen , Müller Daniel J. , Rotzinger Susan , Frey Benicio N. , Kennedy Sidney H , Black Sandra E. , Lang Anthony , Masellis Mario , Symons Sean , Bartha Robert , MacQueen Glenda M ,   The CAN-BIND Investigator Team,   The ONDRI Investigators, Strother Stephen C. 
Published: September 2020

AbstractQuality control of morphometric neuroimaging data is essential to improve reproducibility. Owing to the complexity of neuroimaging data and subsequently the interpretation of their results, visual inspection by trained raters is the most reliable way to perform quality control. Here, we present a protocol for visual quality control of the anatomical accuracy of FreeSurfer parcellations, based on an easy-to-use open source tool called VisualQC. We comprehensively evaluate its utility in terms of error detection rate and inter-rater reliability on two large multi-site datasets, and discuss site differences in error patterns. This evaluation shows that VisualQC is a practically viable protocol for community adoption.
Bioinformatical analysis identified significant genes in the PI3K-Akt signaling pathway relating with poor prognosis of skin cutaneous melanoma
Authors: Zhang Yingzi , Zhang Yunlan , Hu Xuyun 
Published: September 2020

AbstractSkin cutaneous melanoma (SKCM) is the most serious form of skin cancer and the reliable genetic prognostic biomarkers are not clear. The purpose of the present academic work was to identify reliable prognostic biomarkers and understand the underlying mechanism. Gene expression profiles of GSE31909, GSE104849 and GSE111766 were available from Gene Expression Omnibus (GEO). DEGs were collected from 13 melanoma samples and 12 melanocyte samples which were in the three profile datasets by GEO2R analysis. Gene ontology (GO) analysis and KEGG analysis were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID).We further established protein-protein interaction (PPI) and identify core genes with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) app in Cytoscape software. There were total of 63 consistently expressed genes in the three datasets, including eight up-regulated genes enriched in biological processes like osteoblast differentiation and extracellular matrix organization, and cell component like extracellular space, while 55 down-regulated genes enriched in positive regulation of gene expression, intracellular signal transduction, cell adhesion and apoptotic process. With prognostic information and expression data from UALCAN and Gene Expression Profiling Interactive Analysis (GEPIA), we identified three significant genes (TNC, SPP1 and KIT). After Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, all three genes were located in the PI3K-Akt Signaling Pathway. Our results provide additional genetic biomarkers for SKCM patients.
Assessing the influence of climate on future wintertime SARS-CoV-2 outbreaks
Authors: Baker Rachel E. , Yang Wenchang , Vecchi Gabriel A. , Jessica E. Metcalf C. , Grenfell Bryan T. 
Published: September 2020

AbstractHigh susceptibility has limited the role of the climate in the SARS-CoV-2 pandemic to date. However, understanding a possible future effect of climate, as susceptibility declines and the northern-hemisphere winter approaches, is an important open question. Here we use an epidemiological model, constrained by observations, to assess the sensitivity of future SARS-CoV-2 disease trajectories to local climate conditions. We find this sensitivity depends on both the susceptibility of the population and the efficacy of non-pharmaceutical controls (NPIs) in reducing transmission. Assuming high susceptibility, more stringent NPIs may be required to minimize outbreak risk in the winter months. Our results imply a role for meteorological forecasts in projecting outbreak severity, however, reducing uncertainty in epidemiological parameters will likely have a greater impact on generating accurate predictions and reflects the strong leverage of NPIs on future outbreak severity.
Hopeful monsters: Unintended sequencing of famously malformed mite mitochondrial tRNAs reveals widespread expression and processing of sense-antisense pairs
Authors: Warren Jessica M. , Sloan Daniel B. 
Published: September 2020

AbstractAlthough tRNA structure is one of the most conserved and recognizable shapes in molecular biology, aberrant tRNAs are frequently found in the mitochondrial genomes of metazoans. The structure of several mitochondrial tRNAs is so degenerate that doubts have been raised about their expression and function. Mites from the arachnid superorder Acariformes are predicted to have some of the shortest mitochondrial tRNAs, with apparent base mismatches in acceptor stems and a complete loss of cloverleaf-life shape. While performing mitochondrial isolations and recently developed RNA-seq methods to capture mature, CCA-tailed tRNAs in plant tissue, we inadvertently sequenced the mitochondrial tRNAs from a common plant pest, the acariform miteTetranychus urticae,to a high enough coverage to detect all previously annotatedT. urticaetRNA regions. The results not only confirm expression, CCA-tailing and post-transcriptional base modification of these highly divergent tRNAs, but also revealed widespread sense and antisense expression of tRNA genes in theT. urticaemitochondrial genome. Mirrored expression of mitochondrial tRNA genes has been previously hypothesized but not demonstrated to be extensive in any system. We discuss the functional roles that these divergent tRNAs could have as both decoding molecules in translation and processing signals in transcript maturation pathways for other genes, as well as how the surprising finding of sense-antisense tRNA pairs adds another dimension to the bizarre tRNA biology of mitochondrial genomes.
Synaptic plasticity in the orbitofrontal cortex explains how risk attitude adapts to the range of risk prospects
Authors: Brochard Jules , Daunizeau Jean 
Published: September 2020

AbstractMany deleterious behaviors, such as procrastinating on urgent matters or sustaining a toxic relationship, are irrational. But is irrational behavior the incidental outcome of biological constraints imposed on neural information processing? In particular, can those constraints alter decisions, even when people know the consequences of alternative actions? Recent studies indicate that orbitofrontal neurons encode decision value in relative terms, i.e. value signals in OFC neurons are normalized with respect to the context. Value-based decisions may thus exhibit irrational context-dependence effects. A candidate explanation is “efficient coding”: OFC neurons may mitigate information loss by adapting their (bounded) output firing properties to the recent value range. This is seducing, because it suggests that relative value coding is the brain’s best attempt to produce rational behavior, given its own hard-wired biological constraints. However, whether the behavioral implications of this scenario are met, how it generalizes to realistic situations in which OFC neurons construct value from multiple decision-relevant attributes, and what its neurophysiological bases are, is unclear. Here, we address these issues by re-analyzing two open fMRI datasets from theOpenNeuro.orginitiative, where people have to integrate prospective gains and losses to decide whether to gamble or not. First, we show that peoples’ risk attitudes critically depend on the range of gain prospects they are exposed to. Importantly, counter to simple efficient coding scenarios, differences in gain ranges induce progressive changes in peoples’ sensitivity to both gains and losses. Second, we use artificial neural network models to show that hebbian rewiring processes between attribute-specific and attribute-integration neurons predict (out-of-sample) both context-dependence effects in peoples’ risk attitude and multivariate patterns of fMRI activity in the OFC. Under mild conditions on distributed population codes for decision attributes, hebbian plasticity eventually translates the distribution of reweighted attribute signals towards the responsive range of integration neurons. In turn, integration units exhibit the known features of range adaptation, including (but not limited to), relative value coding. Our results demonstrate how hebbian plasticity within brain networks may result in range adaptation, eventually yielding complex though predictable irrational behavior.
The erosion of biodiversity and biomass in the Atlantic Forest biodiversity hotspot
Authors: Lima Renato A. F. , Oliveira Alexandre A. , Pitta Gregory R. , de Gasper André L. , Vibrans Alexander C. , Chave Jérôme , ter Steege Hans , Prado Paulo I. 
Published: September 2020

AbstractTropical forests are being deforested worldwide, and the remaining fragments are suffering from biomass and biodiversity erosion. Quantifying this erosion is challenging because ground data on tropical biodiversity and biomass are often sparse. Here, we use an unprecedented dataset of 1,819 field surveys covering the entire Atlantic Forest biodiversity hotspot. We show that 83–85% of the surveys presented losses in forest biomass and tree species richness, functional traits and conservation value. On average, forest fragments had 25–32% less biomass, 23–31% fewer species, and 33%, 36% and 42% fewer individuals of late-successional, large-seeded and endemic species, respectively. Biodiversity and biomass erosion were both lower inside strictly protected conservation units, particularly in large ones. We estimate that biomass erosion across the Atlantic Forest remnants was equivalent to the loss of 55-70 thousand km2of forests or US$2.3-2.6 billion in carbon credits. These figures have direct implications on mechanisms of climate change mitigation.
Peripheral blood mononuclear cells preferentially activate 11-oxygenated androgens
Authors: Schiffer Lina , Bossey Alicia , Taylor Angela E , Akerman Ildem , Scheel-Toellner Dagmar , Storbeck Karl-Heinz , Arlt Wiebke 
Published: September 2020

AbstractContextAndrogens are important modulators of immune cell function impacting proliferation, differentiation and cytokine production. The local generation of active androgens from circulating androgen precursors is an important mediator of androgen action in peripheral androgen target cells or tissue.ObjectiveTo characterize the activation of classic and 11-oxygenated androgens in human peripheral blood mononuclear cells (PBMCs).MethodsPBMCs were isolated from healthy male donors and incubated ex vivo with precursors and active androgens of the classic and 11-oxygenated androgen pathways. Steroids were quantified by liquid chromatography-tandem mass spectrometry. The expression of genes encoding steroid-metabolizing enzymes was assessed by quantitative PCR.ResultsPBMCs generated 8-fold higher amounts of the active 11-oxygenated androgen 11-ketotestosterone than the classic androgen testosterone from their respective precursors. We identified the enzyme AKR1C3 as the major reductive 17β-hydroxysteroid dehydrogenase in PBMCs responsible for both conversions and found that within the PBMC compartment natural killer cells are the major site of AKRC13 expression and activity. Steroid 5α-reductase type 1 catalyzed the 5α-reduction of classic but not 11-oxygenated androgens in PBMCs. Lag time prior to the separation of cellular components from whole blood increased 11KT serum concentrations in a time-dependent fashion, with significant increases detected from two hours after blood collection.Conclusions11-oxygenated androgens are the preferred substrates for androgen activation by AKR1C3 in PBMCs, primarily conveyed by natural killer cell AKR1C3 activity, yielding 11KT the major active androgen in PBMCs. Androgen metabolism by PBMCs can affect the measurement results of serum 11-ketotestosterone concentrations, if samples are not separated in a timely fashion.
Single-Cell Resolution of Lineage Trajectories in the Arabidopsis Stomatal Lineage and Developing Leaf
Authors: Lopez-Anido Camila B. , Vatén Anne , Smoot Nicole K. , Sharma Nidhi , Guo Victoria , Gong Yan , Anleu Gil M. Ximena , Weimer Annika K. , Bergmann Dominique C. 
Published: September 2020

SUMMARYDynamic cell states underlie flexible developmental programs, such as with the stomatal lineage of the Arabidopsis epidermis. Initial stages of the lineage feature asynchronous and indeterminate divisions modulated by environmental cues, enabling cell fate flexibility to generate the requisite density and pattern of stomata for a given environment. It remains unclear, however, how flexibility of cell fates is controlled. Here, we uncovered distinct models of cell state differentiation within Arabidopsis leaf tissue by leveraging single-cell transcriptomics and molecular genetics. Our findings resolved underlying heterogeneity within cell states of the flexible epidermal stomatal lineage, which appear to exist along a continuum, with progressive cell specification. Beyond the early stages of the lineage, we discovered that the core transcriptional regulator SPEECHLESS is required for cell fate commitment to yield stomatal guard cells. Overall, our work has refined the stomatal lineage paradigm and uncovered progressive cell state decisions along lineage trajectories in developing leaves.