bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Flower power”: how flowering affects spectral diversity metrics and their relationship with plant diversity
Authors: Perrone Michela , Conti Luisa , Galland Thomas , Komárek Jan , Lagner Ondřej , Torresani Michele , Rossi Christian , Carmona Carlos P. , Bello Francesco de , Rocchini Duccio , Moudrý Vítězslav , Šímová Petra , Bagella Simonetta , Malavasi Marco 
Published: December 2023

AbstractBiodiversity monitoring is constrained by cost- and labour-intensive field sampling methods. Increasing evidence suggests that remotely sensed spectral diversity (SD) is linked to plant diversity, holding promise for monitoring applications. However, studies testing such a relationship reported conflicting findings, especially in challenging ecosystems such as grasslands, due to their high temporal dynamism and variety. It follows that a thorough investigation of the key factors, such as the metrics applied (i.e., continuous, categorical) and phenology (e.g., flowering), influencing such a relationship is necessary. Thus, this study aims to assess the applicability of SD for plant diversity monitoring at the local scale by testing six different SD metrics while considering the effect of the presence of flowering on the relationship and resampling the original data to assess how spatial resolution affects the results. Taxonomic diversity was calculated based on data collected in 159 plots with 1.5 m ×1.5 m experimental mesic grassland communities. Spectral information was collected using a UAV-borne sensor measuring reflectance across six bands in the visible and near-infrared range at ∼2 cm spatial resolution. Our results show that, in the presence of flowering, the relationship is significant and positive only when SD is calculated using categorical metrics. Despite the observed significance, the variance explained by the models had very low values, with no evident differences when resampling spectral data to coarser pixel sizes. Such findings suggest that new insights into the possible confounding effects on the SD∼plant diversity in grassland communities are needed to use SD for monitoring purposes.
Globally abundant birds disproportionately inhabit anthropogenic environments
Authors: Carroll Tadhg , Hatfield Jack H. , Thomas Chris D. 
Published: December 2023

AbstractResearch into biodiversity change predominantly focuses on rarity and declines, but many ecological processes are governed by abundant species. Analysing 3,146 terrestrial bird species across 5,454 field-sampled sites, we find that three times more species in the top quartile for global abundance are more likely to occur in ecosystems characterised by major human land-cover modification (croplands, plantation forest, urban areas and pasture), compared with species in the bottom quartile. The likelihood of inhabiting human-modified environments consistently increases with global abundance across species with different dietary requirements, whereas low abundance species tend to have increased probabilities of occurrence (within their ranges) in relatively unmodified environments. Our findings suggest that human modification of the Earth’s land surface has favoured ‘anthrophilic’ species able to thrive in widespread anthromes.One-Sentence SummaryThe world’s most abundant birds disproportionately inhabit croplands, plantation forests, urban areas and pastures.
Characterization ofStreptococcus uberisCas9 (SuCas9) – a Type II-A Ortholog Functional in Human Cells
Authors: Selkova Polina , Vasileva Aleksandra , Arseniev Anatolii , Abramova Marina , Musharova Olga , Malysheva Polina , Khodorkovskii Mikhail , Severinov Konstantin 
Published: December 2023

AbstractType II CRISPR-Cas9 RNA-guided nucleases are commonly used for genome engineering. To date, all characterized Cas9-based genome editors, including the widely used SpCas9, have limitations such as their relatively large size and restriction of targets flanked by a specific PAM sequence. Here, we biochemically characterized more compact SpCas9 ortholog, SuCas9, fromStreptococcus uberis, a bacterium inhabiting the mammary glands of dairy cattle. SuCas9 recognizes a novel 5′-NNAAA-3′ PAM, efficiently cleaves DNAin vitro, and is active in human cells. The study of SuCas9 has the potential to expand the range of applications of CRISPR-Cas9 enzymes in medicine and biotechnology.
Postnatal FGFR-signaling establishes gradients of secretory cell identities along the proximal-distal axis of the lung airways
Authors: Sountoulidis Alexandros , Firsova Alexandra B. , Liontos Andreas , Theelke Jonas , Koepke Janine , Millar-Büchner Pamela , Mannerås-Holm Louise , Björklund Åsa , Fysikopoulos Athanasios , Gaengel Konstantin , Bäckhed Fredrik , Betsholtz Christer , Seeger Werner , Bellusci Saverio , Samakovlis Christos 
Published: December 2023

AbstractSecretory cells are major structural and functional constituents of the lung airways. Their spatial organization and specification mechanisms are partially understood. Here, we labelled major secretory airway cell types and analysed them at single-cell resolution. We found opposing, partially overlapping gene-expression gradients along the proximal-distal airway axis superimposed on a general gene program encoding detoxification. One graded program is elevated proximally and relates to innate immunity, whereas the other is enriched distally, encoding lipid metabolism and antigen presentation. Intermediately positioned cells express low levels of both graded programs and show increased clonogenic potency in vitro, relating cell-plasticity to location in each branch. Single-cell RNA-sequencing following lineage-tracing revealed the sequential and postnatal establishment of the gradients in common epithelial progenitors. Fgfr2b is distally enriched and its postnatal inactivation reduces distal gene expression and expands proximal genes into distally located cells. This suggests a central role of FGFR-signaling in tissue-scale airway patterning.
Climate change has desynchronized insect and vegetation phenologies across Europe
Authors: Huang Yanru , Wu Chaoyang , Huang Wenjiang , Liu Yang , Qi Man , Bai Jie , Dong Yingying , Gascoigne Samuel J L , Ciais Philippe , Peñuelas Josep , Salguero-Gómez Roberto 
Published: December 2023

SummaryClimate change is drastically affecting the phenologies of species worldwide, including shifts in development1–3. The potential impact of climate change on the synchronicity of plant-insect phenology is particularly concerning since the stability of pollination networks and food chains depends on their tight temporal dependencies4–6. Furthermore, the recently reported “insect armageddon”7makes it urgent to establish trends and identify primary drivers of plant-insect phenological synchrony. Here, coupling high-resolution remote sensing and citizen science data across Europe over 34 years, we examine the differences in occurrence dates of 1,584 herbivorous insects across four orders and the corresponding dates of leaf unfolding. We find that 61.2% of the vegetation and insect phenologies have become highly asynchronous, with vegetation phenology advancing four-fold faster than insect phenology. These trends were modulated by insects’ life-cycles and taxonomic order. A primary driver of this phenological mismatch is the higher sensitivity of vegetation phenology than insect phenology to climate, which has prevented insects from matching the pace of plant phenological advance in the growing season. Our analyses provide a unique continental overview and underlying mechanisms of the asynchronicity between vegetation and insect phenologies, thus enhancing our ability to predict and manage its potential cascading ecological effects.
Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types
Authors: Lin Yao , Li Jingyi , Liang Shuaiyi , Chen Yaxin , Li Yueqi , Cun Yixian , Tian Lei , Zhou Yuanli , Chen Yitong , Chu Jiemei , Chen Hubin , Luo Qiang , Zheng Ruili , Wang Gang , Liang Hao , Cui Ping , An Sanqi 
Published: December 2023

AbstractAs the most abundant mRNA modification in mRNA,N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A-seq and RNA-seq samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called “m6A-express”, we predicted m6A– regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulatorCAPRIN1controls the m6A level ofTP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.
scPharm: identifying pharmacological subpopulations of single cells for precision medicine in cancers
Authors: Tian Peng , Zheng Jie , Xu Yue , Wu Tao , Chen Shuting , Zhang Yinuo , Zhang Bingyue , Qiao Keying , Fan Yuxiao , Ambrogio Chiara , Wang Haiyun 
Published: December 2023

AbstractIntratumour heterogeneity is a major challenge that limits the effectiveness of anticancer therapies, thus compromising treatment outcomes. Single-cell RNA sequencing (scRNA-seq) technology offers a means to capture gene expression profiles at a single-cell resolution, while drug perturbation experiments yield valuable pharmacological data at the bulk cell level. Here, we introduce “scPharm”, a computational framework to integrate large-scale pharmacogenomics profiles with scRNA-seq data, for identifying pharmacological subpopulations within a tumour and prioritizing tailored drugs. scPharm assesses the distribution of the identity genes of single cell (Cell-ID) within drug response-determined gene list, which is accomplished using the normalized enrichment score (NES) obtained from Gene Set Enrichment Analysis (GSEA) as the statistic. One key strength of scPharm is rooted in the robust positive correlation between NES statistics and drug response values at single-cell resolution. scPharm successfully identifies sensitive subpopulations in ER-positive and HER2-positive human breast cancer tissues, discovers dynamic changes in resistant subpopulation of human PC9 cells treated with Erlotinib, and expands its prediction capabilities to a mouse model. By a thoroughly comparative evaluation with other single-cell prediction tools, scPharm presents the superior predictive performance and computational efficiency. Furthermore, scPharm offers a unique feature by predicting combination strategies, gauging compensation effects or booster effects between two drugs through the Set covering method, as well as evaluating drug toxicity on healthy cells within the tumour microenvironment. Together, scPharm provides a novel approach to uncover therapeutic heterogeneity within tumours at single-cell resolution and facilitates precision medicine in cancers.
AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance
Authors: Raisinghani Nishank , Alshahrani Mohammed , Gupta Grace , Xiao Sian , Tao Peng , Verkhivker Gennady 
Published: December 2023

AbstractIn this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.
Statistical models of hospital patient fatality rates after accidental falls in children
Authors: Rossant Cyrille , Schneps Leila 
Published: December 2023

ABSTRACTPediatric traumatic brain injuries represent a public health concern globally. Epidemiological studies are essential to understand their extent, uncover risk factors and outcome predictors, and establish efficient prevention policies. Etiological investigations also benefit from epidemiological data. In young, pre-linguistic children, distinguishing between accidental and non-accidental trauma is often challenging for frontline clinicians. Classification errors can have severe repercussions for children and their families. Past influential epidemiological studies have drawn general conclusions about the etiology of pediatric traumatic brain injuries based on specific statistical information, such as hospital patient fatality rates after reported accidental falls. In this article, we use simple mathematical models to revisit one of these studies and discuss the reliability of its conclusion. We show that apparent paradoxical discrepancies, such as hospital patient fatality rates that are higher after short versus long falls, may have mathematical justification and do not necessarily justify seeking alternative etiological explanations such as non-accidental trauma.
Dissecting the Impact of Maternal Androgen Exposure on Offspring Health through Targeting the Androgen Receptor in Developmental Programming
Authors: Lu Haojiang , Jiang Hong , Li Congru , Derisoud Emilie , Zhao Allan , Eriksson Gustaw , Lindgren Eva , Pui Han-Pin , Risal Sanjiv , Pei Yu , Maxian Theresa , Ohlsson Claes , Benrick Anna , Haider Sandra , Stener-Victorin Elisabet , Deng Qiaolin 
Published: December 2023

AbstractWomen with polycystic ovary syndrome (PCOS) exhibit sustained elevation in circulating androgens during pregnancy, an independent risk factor linked to pregnancy complications and adverse neonatal outcomes. Yet, further investigation is required to understand the precise mechanisms and the impact on cell-type specific placental dysfunction. To explore these dynamics, a PCOS-like mice model was induced with continuous androgen exposure throughout pregnancy, mimicking the human-PCOS. This resulted in impaired placental and embryonic development, leading to mid-gestation lethality. Co-treatment with the androgen receptor blocker, flutamide, prevented this lethality. Comprehensive analysis using whole-genome bisulfite and RNA sequencing revealed the diminished proportion of trophoblast precursors by downregulation ofCdx2. The absence ofGcm1,Synb,andPrl3b1further resulted in decreased numbers of syncytiotrophoblasts and sinusoidal trophoblast giant cells, leading to observed compromised placenta labyrinth formation. Importantly, human trophoblast organoids exposed to androgens exhibited analogous alterations, highlighting impaired trophoblast differentiation as a key feature in PCOS-related pregnancy complications. Remarkably, all effects were mediated through the androgen receptor pathways, as demonstrated by comparable offspring phenotypes to controls when treated with flutamide. These findings provide novel insight into the PCOS-related pregnancy complications, and potential cellular targets for future treatment.
Molecular signature of primate astrocytes reveals pathways and regulatory changes contributing to the human brain evolution
Authors: Ciuba K. , Piotrowska A. , Chaudhury D. , Dehingia B. , Duński E. , Behr R. , Soroczyńska K. , Czystowska-Kuźmicz M. , Abbas M. , Figiel I. , Włodarczyk J. , Verkhratsky A. , Niedbała M. , Kaspera W. , Wilczyński B. , Pękowska A. 
Published: December 2023

AbstractAstrocytes contribute to the development and regulation of the higher-level functions of the brain, the critical targets of evolution. However, the molecular signature of foetal astrocyte evolution in primates is unknown. Here, to address this question, we use human, chimpanzee, and macaque induced pluripotent stem cell-derived foetal astrocytes (iAstrocytes). Human iAstrocytes are bigger and more complex than the non-human primate iAstrocytes. We find loci related to the regulation of cell size with increased expression in the human lineage. Likewise, we uncover that genes and mechanisms implicated in long-range intercellular signalling are activated in the human iAstrocytes. Strikingly, loci downregulated in the human lineage frequently relate to intellectual disability raising new questions on the trade-offs associated with the evolution of the human mind. Using our system, through a multilevel regulome analysis and machine learning, we uncover that functional activation of enhancers coincides with a previously unappreciated, pervasive gain of binding sites of ‘stripe’ transcription factors. In summary, we shed new light on a mechanism driving the acquisition of the regulatory potential of enhancers.
Using feedback in pooled experiments augmented with imputation for high genotyping accuracy at reduced cost
Authors: Clouard Camille , Nettelblad Carl 
Published: December 2023

AbstractConducting genomic selection in plant breeding programs can substantially speed up the development of new varieties. Genomic selection provides more reliable insights when it is based on dense marker data, in which the rare variants can be particularly informative while they are delicate to capture with sufficient statistical power. Despite the release of new performing technologies, the cost of large-scale genotyping remains a major limitation to the implementation of genomic selection. We suggest to combine pooled genotyping with population-based imputation as a cost-effective computational strategy for genotyping SNPs. Pooling saves genotyping tests and has proven to accurately capture the rare variants that are usually missed by imputation. In this study, we investigate an extension to our joint model of pooling and imputation via iterative coupling. In each iteration, the imputed genotype probabilities serve as feedback input for rectifying the decoded data, before running a new imputation in these adjusted data. Such flexible set up indirectly imposes consistency between the imputed genotypes and the pooled observations. We demonstrate that repeated cycles of feedback can take full advantage of the strengths in both pooling and imputation. The iterations improve greatly upon the initial genotype predictions, achieving very high genotype accuracy for both low and high frequency variants. We enhance the average concordance from 94.5% to 98.4% at a very limited computational cost and without requiring any additional genotype testing. We believe that these results could be of interest for plant breeders and crop scientists.Author summaryIn applications such as large-scale population surveys or plant breeding, the cost of genetic testing can limit the number of samples that are genotyped, or force the reduction to more cost-effective low-density marker panels. A reduction in the number of samples or the number of variants surveyed can reduce the power to detect important genetic correlations. We propose a scheme of pooled genotype testing, which would allow for using half the number of test assays for the same number of individuals surveyed. The data from overlapping pool tests is augmented with genotype imputation. We have previously shown that this approach was competitive, but with some drawbacks. Most strikingly, the error rate for common variants could be in the range of 10%. Now, we propose a new computational method for reconstructing SNP genotypes with pooling and imputation, adding an iterative coupled model connecting the two. This model allows us to exploit the advantages of both methods and achieves consistently high genotype reconstruction accuracy. We demonstrate the performance of our approach on a hypothetical plant breeding application based on a public genetic dataset from wheat samples. However, main aspects of the methodology would translate to many other settings.
Diversity in recombination hotspot characteristics and gene structure shape fine-scale recombination patterns in plant genomes
Authors: Brazier Thomas , Glémin Sylvain 
Published: December 2023

AbstractDuring the meiosis of many eukaryote species, crossovers tend to occur within narrow regions called recombination hotspots. In plants, it is generally thought that gene regulatory sequences, especially promoters and 5’-3’ untranslated regions, are enriched in hotspots, but this has been characterized in a handful of species only. We also lack a clear description of fine-scale variation in recombination rates within genic regions and little is known about hotspot position and intensity in plants. To address this question we constructed fine-scale recombination maps from genetic polymorphism data and inferred recombination hotspots in eleven plant species. We detected gradients of recombination both in 5’ and 3’ of genic regions in most species, yet gradients varied in intensity and shape depending on specific hotspot locations and gene structure. To further characterize recombination gradients, we decomposed them according to gene structure by rank and number of exons. We generalized the previously observed pattern that recombination hotspots are organized around the boundaries of coding sequences, especially 5’ promoters. However, our results also provided new insight into the relative importance of the 3’ end of genes in some species and the possible location of hotspots away from genic regions in some species. Variation among species seemed driven more by hotspot location among and within genes than by differences in size or intensity among species. Our results shed light on the variation in recombination rates at a very fine scale, more detailed than whole genome averaged estimates used so far, revealing the diversity and complexity of genic recombination gradients emerging from the interaction between hotspot location and gene structure.