bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global terrestrial nitrogen uptake and nitrogen use efficiency
Authors: Peng Yunke , Prentice Iain Colin , Bloomfield Keith J. , Campioli Matteo , Guo Zhiwen , Sun Yuanfeng , Tian Di , Wang Xiangping , Vicca Sara , Stocker Benjamin D. 
Published: November 2022

AbstractPlant biomass production (BP), nitrogen uptake (Nup) and their ratio, nitrogen use efficiency (NUE), must be quantified to understand how nitrogen (N) cycling constrains terrestrial carbon (C) uptake. But the controls of key plant processes determiningNupand NUE, including BP, C and N allocation, tissue C:N ratios and N resorption efficiency (NRE), remain poorly known. We compiled measurements from 804 forest and grassland sites and derived regression models for each of these processes with growth temperature, vapour pressure deficit, stand age, soil C:N ratio, fAPAR (remotely sensed fraction of photosynthetically active radiation absorbed by green vegetation) and growing-season average daily incident photosynthetic photon flux density (gPPFD) (effectively the seasonal concentration of light availability, which increases polewards) as predictors. An empirical model for leaf N was based on optimal photosynthetic capacity (a function of gPPFD and climate) and observed leaf mass-per-area. The models were used to produce global maps ofNupand NUE. Global BP was estimated as 72 Pg C/yr;Nupas 950 Tg N/yr; and NUE as 76 gC/gN. Forest BP was found to increase with growth temperature and fAPAR and to decrease with stand age, soil C:N ratio and gPPFD. Forest NUE is controlled primarily by climate through its effect on C allocation – especially to leaves, being richer in N than other tissues. NUE is greater in colder climates, where N is less readily available, because belowground allocation is increased. NUE is also greater in drier climates because leaf allocation is reduced. NRE is enhanced (further promoting NUE) in both cold and dry climates. These findings can provide observationally based benchmarks for model representations of C–N cycle coupling. State-of-the-art vegetation models in the TRENDY ensemble showed variable performance against these benchmarks, and models including coupled C–N cycling produced relatively poor simulations ofNupand NUE.
Research and conservation priorities to protect wildlife from collisions with vehicles
Authors: Medrano-Vizcaíno Pablo , Grilo Clara , González-Suárez Manuela 
Published: November 2022

AbstractThe rapidly expanding global road network poses threats to wildlife, including direct mortality. Given limited knowledge and resources, strategic allocation is critical. We introduce a method to identify priority areas and taxa to study and protect affected by vehicle collisions using Latin America as a case study. In this region high biodiversity and an expanding road network can result in high impacts from roads, yet emerging research expertise offers opportunities for action. To identify priority targets we combined predicted spatially-explicit roadkill rates for birds and mammals with information about the current road network and species conservation status. Priority areas for conservation (with many species susceptible to roadkill but few or inexistent roads) were largely concentrated in the Amazon; while priority areas for research (unstudied regions with many roads and many species susceptible to roadkill) occur in various areas from Southern Mexico to Chile. Priority taxa for conservation reflected studied, roadkill-susceptible groups (eg, vultures and armadillos), while priority taxa for research were defined as either poorly-studied roadkill-susceptible groups or unstudied groups of conservation concern (eg, cuckoos and shrew opossums). Our approach offers a tool that could be applied to other areas and taxa to facilitate a more strategic allocation of resources in conservation and research in road ecology.
Identifying cross-lineage dependencies of cell-type specific regulators in gastruloids
Authors: Braccioli Luca , van den Brand Teun , Saiz Noemi Alonso , Fountas Charis , Celie Patrick H. N. , Kazokaitė-Adomaitienė Justina , de Wit Elzo 
Published: November 2022

AbstractCorrect gene expression levels in space and time are crucial for normal development. Advances in genomics enable the inference of gene regulatory programs that are active during development. However, this approach cannot capture the complex multicellular interactions that occur during embryogenesis. Compared to model organisms such as fruit flies and zebrafish, the growth of mammalian embryosin uterofurther complicates the analysis of cell-cell communication during development. However,in vitromodels of mammalian development such as gastruloids can overcome this limitation. Using time-resolved single-cell chromatin accessibility analysis, we have delineated the regulatory landscape during gastruloid development and thereby identified the critical drivers of developmental transitions. We observed that gastruloids develop from pluripotent cells driven by the transcription factor (TF) dimer OCT4-SOX2 and differentiate along two main branches. A mesoderm branch characterized by the TF MSGN1 and a spinal cord branch characterized by CDX1, 2, 4 (CDX). Consistent with our lineage reconstruction, ΔCDX gastruloids fail to form spinal cord. Conversely,Msgn1ablation inhibits the development of paraxial mesoderm, as expected. However, this also abolished spinal cord cells, which is surprising given that MSGN1 is not associated with differentiation along this branch. Therefore, formation of paraxial mesoderm is required for spinal cord development. To validate this, we generated chimeric gastruloids using ΔMSGN1 and wildtype cells, which formed both spinal cord and paraxial mesoderm. Strikingly, ΔMSGN1 cells specifically contributed to spinal cord, suggesting that cell-cell interactions between paraxial mesoderm and spinal cord are necessary for the formation of the latter. Our work has important implications for the study of cell-cell communication in development and how gene regulatory programs are functionally executed to form complex multicellular developmental structures.
Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data
Authors: Augustin David , Lambert Ben , Wang Ken , Walz Antje-Christine , Robinson Martin , Gavaghan David 
Published: November 2022

AbstractVariability is an intrinsic property of biological systems and is often at the heart of their complex behaviour. Examples range from cell-to-cell variability in cell signalling pathways to variability in the response to treatment across patients. A popular approach to model and understand this variability is nonlinear mixed effects (NLME) modelling. However, estimating the parameters of NLME models from measurements quickly becomes computationally expensive as the number of measured individuals grows, making NLME inference intractable for datasets with thousands of measured individuals. This shortcoming is particularly limiting for snapshot datasets, common e.g. in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. We extend earlier work by Hasenauer et al (2011) to introduce a novel approach for the estimation of NLME model parameters from snapshot measurements, which we call filter inference. Filter inference is a new variant of approximate Bayesian computation, with dominant computational costs that do not increase with the number of measured individuals, making efficient inferences from snapshot measurements possible. Filter inference also scales well with the number of model parameters, using state-of-the-art gradient-based MCMC algorithms, such as the No-U-Turn Sampler (NUTS). We demonstrate the properties of filter inference using examples from early cancer growth modelling and from epidermal growth factor signalling pathway modelling.Author summaryNonlinear mixed effects (NLME) models are widely used to model differences between individuals in a population. In pharmacology, for example, they are used to model the treatment response variability across patients, and in cell biology they are used to model the cell-to-cell variability in cell signalling pathways. However, NLME models introduce parameters, which typically need to be estimated from data. This estimation becomes computationally intractable when the number of measured individuals – be they patients or cells – is too large. But, the more individuals are measured in a population, the better the variability can be understood. This is especially true when individuals are measured only once. Such snapshot measurements are particularly common in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. In clinical pharmacology, datasets consisting of many snapshot measurements are less common but are easier and cheaper to obtain than detailed time series measurements across patients. Our approach can be used to estimate the parameters of NLME models from snapshot time series data with thousands of measured individuals.
“An optimized pipeline for live imaging whole Arabidopsis leaves at cellular resolution”
Authors: Harline Kate , Roeder Adrienne 
Published: November 2022

AbstractLive imaging is the gold standard for determining how cellular development gives rise to organs. However, tracking all individual cells across whole organs over large developmental time windows is extremely challenging. In this work, we provide a comparably simple method for confocal live imaging ofArabidopsis thalianafirst leaves across early development. Our imaging method works for both wild-type leaves and the complex curved leaves of thejaw-1Dmutant. We find that dissecting the cotyledons, affixing a coverslip above the samples and mounting samples with perfluorodecalin yields optimal imaging series for robust cellular and organ level analysis. We provide details of our complementary image processing steps in MorphGraphX software for segmenting cells, tracking the cell lineages, and measuring a suite of cellular growth properties. We also provide MorphoGraphX image processing scripts that we developed to automate analysis of segmented images and data presentation. Our imaging techniques and processing steps combine into a robust imaging pipeline. With this pipeline we are able to examine important nuances in the cellular growth and differentiation ofjaw-Dversus WT leaves that have not been demonstrated before. Our pipeline is a practical starting place for researchers new to live imaging plant leaves, but also to anyone interested in improving the throughput and reliability of their live imaging process.
The circadian clock is disrupted in pancreatic cancer
Authors: Schwartz Patrick B. , Nukaya Manabu , Berres Mark E. , Rubinstein Clifford D. , Wu Gang , Hogenesch John B. , Bradfield Christopher A. , Ronnekleiv-Kelly Sean M. 
Published: November 2022

AbstractDisruption of the circadian clock is linked to cancer development and progression. Establishing this connection has proven beneficial for understanding cancer pathogenesis, determining prognosis, and uncovering novel therapeutic targets. However, barriers to characterizing the circadian clock in human pancreas and human pancreatic cancer – one of the deadliest malignancies – have hindered an appreciation of its role in this cancer. Here, we employed normalized coefficient of variation (nCV) and clock correlation analysis in human population-level data to determine the functioning of the circadian clock in pancreas cancer and adjacent normal tissue. We found a substantially attenuated clock in the pancreatic cancer tissue. Then we exploited our existing mouse pancreatic transcriptome data to perform an analysis of the human normal and pancreas cancer samples using a machine learning method, cyclic ordering by periodic structure (CYCLOPS). Through CYCLOPS ordering, we confirmed the nCV and clock correlation findings of an intact circadian clock in normal pancreas with robust cycling of several core clock genes. However, in pancreas cancer, there was a loss of rhythmicity of many core clock genes with an inability to effectively order the cancer samples, providing substantive evidence of a dysregulated clock. The implications of clock disruption were further assessed with aBmal1knockout pancreas cancer model, which revealed that an arrhythmic clock caused accelerated cancer growth and worse survival, accompanied by chemoresistance and enrichment of key cancer-related pathways. These findings provide strong evidence for clock disruption in human pancreas cancer and demonstrate a link between circadian disruption and pancreas cancer progression.Author SummaryThe circadian clock is a regulator of human homeostasis. Dysfunction of the clock can lead to the development of diseases, including cancer. Although several cancers have been shown to have a dysfunctional clock which may alter prognosis or change treatment, this has been suggested but not demonstrated in pancreatic cancer. Investigation of this link is important because pancreatic cancer is highly lethal with few effective treatment options. Here we use recently pioneered bioinformatics approaches to assess clock functionality in human pancreatic cancer specimens, where we demonstrate that the clock is dysfunctional relative to normal pancreatic tissue. We then knocked out the core clock gene,Bmal1, in pancreatic cancer cells, which led to faster tumor growth and worse survival in mice and enhanced chemotherapeutic resistance to standard chemotherapy agents used in the treatment of pancreatic cancer. Collectively, our findings establish human pancreatic cancer as having clock dysfunction and clock dysfunction causing a more aggressive cancer.
Targeting BET Proteins downregulates miR-33a to promote synergy with PIM inhibitors in CMML
Authors: Letson Christopher T. , Balasis Maria E. , Newman Hannah , Binder Moritz , Vedder Alexis , Kinose Fumi , Ball Markus , Kruer Traci , Quintana-Gonzalez Ariel , Lasho Terra L. , Finke Christy M. , Almada Luciana L. , Grants Jennifer M. , Zhang Guolin , Fernandez-Zapico Martin E. , Gaspar-Maia Alexandre , Lancet Jeffrey , Komrokji Rami , Haura Eric , Reuther Gary W. , Karsan Aly , Rix Uwe , Patnaik Mrinal M. , Padron Eric 
Published: November 2022

SummaryPreclinical studies in myeloid neoplasms have demonstrated efficacy of Bromodomain and Extra-Terminal protein inhibitors (BETi). However, BETi demonstrate poor single agent activity in clinical trials. Several studies suggest that combination with other anti-cancer inhibitors may enhance the efficacy of BETi. To nominate BETi combination therapies for myeloid neoplasms, we used a chemical screen with therapies currently in clinical cancer development. We identified PIM inhibitors (PIMi) as therapeutically synergistic with BETi in myeloid leukemia models. Mechanistically, we show that PIM kinase is increased after BETi treatment, and that PIM kinase upregulation is sufficient to induce resistance to BETi and sensitize cells to PIMi. Further, we demonstrate that miR-33a downregulation is the underlying mechanism driving PIM1 upregulation. We also show that GM-CSF hypersensitivity, a hallmark of chronic myelomonocytic leukemia (CMML), represents a molecular signature for sensitivity to combination therapy and credential this using patient-derived xenografts supporting the clinical investigation of this combination.
The Choice of Reference Frame Alters Interpretations of Non-Linear Gait
Authors: Ho Tyler K. , Kreter Nicholas , Jensen Cameron B. , Fino Peter C. 
Published: November 2022

ABSTRACTIntroductionHumans regularly follow non-linear trajectories, such as turning, during everyday ambulation. However, globally-defined and locally-defined reference frames fall out of alignment during non- linear locomotion, which complicates spatiotemporal and biomechanical analyses of gait. Thus, the choice of the locally-defined reference frame is an important methodological consideration. This study investigated how different definitions of reference frame change the results and interpretations of common gait measures.MethodsNine healthy adults completed two walking trials around a circular track. Kinematic data were collected via motion capture and used to calculate step length, step width, anteroposterior margin of stability, and mediolateral margin of stability using three different locally-defined reference frames: walkway-fixed, body-fixed, and trajectory-fixed. Linear-mixed effects models compared the effect of reference frame on each gait measure, and the effect of reference frame on conclusions about a known effect of turning gait – asymmetrical stepping patterns.ResultsAll four gait measures differed significantly across the three reference frames. A significant interaction of reference frame and step type (i.e. inside vs outside step) on all four gait measures (p< 0.001) indicated conclusions about asymmetry differed based on the choice of reference frame.ConclusionThe choice of reference frame will change the calculated gait measures and may alter the conclusions of studies investigating non-linear gait. Care should be taken when comparing studies that used different reference frames, as results cannot be easily harmonized. Future studies of non-linear gait need to justify and detail their choice of reference frame.
Phase-separating pyrenoid proteins form complexes in the dilute phase
Authors: He Guanhua , GrandPre Trevor , Wilson Hugh , Zhang Yaojun , Jonikas Martin C. , Wingreen Ned S. , Wang Quan 
Published: November 2022

AbstractWhile most studies of biomolecular phase separation have focused on the condensed phase, relatively little is known about the dilute phase. Theory suggests that stable complexes form in the dilute phase of two-component phase-separating systems, impacting phase separation; however, these complexes have not been interrogated experimentally. We show that such complexes indeed exist, using anin vitroreconstitution system of a phase-separated organelle, the algal pyrenoid, consisting of purified proteins Rubisco and EPYC1. Applying fluorescence correlation spectroscopy (FCS) to measure diffusion coefficients, we found that complexes form in the dilute phase with or without condensates present. The majority of these complexes contain exactly one Rubisco molecule. Additionally, we developed a simple analytical model which recapitulates experimental findings and provides molecular insights into the dilute phase organization. Thus, our results demonstrate the existence of protein complexes in the dilute phase, which could play a significant role in the stability, dynamics, and regulation of condensates.
Tracking SARS-CoV-2 genomic variants in wastewater sequencing data withLolliPop
Authors: Dreifuss David , Topolsky Ivan , Icer Baykal Pelin , Beerenwinkel Niko 
Published: November 2022

AbstractDuring the COVID-19 pandemic, wastewater-based epidemiology has progressively taken a central role as a pathogen surveillance tool. Tracking viral loads and variant outbreaks in sewage offers advantages over clinical surveillance methods by providing unbiased estimates and enabling early detection. However, wastewater-based epidemiology poses new computational research questions that need to be solved in order for this approach to be implemented broadly and successfully. Here, we address the variant deconvolution problem, where we aim to estimate the relative abundances of genomic variants from next-generation sequencing data of a mixed wastewater sample. We introduceLolliPop, a computational method to solve the variant deconvolution problem by simultaneously solving least squares problems and kernel-based smoothing of relative variant abundances from wastewater time series sequencing data. We derive multiple approaches to compute confidence bands, and demonstrate the application of our method to data from the Swiss wastewater surveillance efforts.
Multiplexed neuropeptide mapping in ant brains integrating microtomography and 3D mass spectrometry imaging
Authors: Geier Benedikt , Gil-Mansilla Esther , Liutkeviciute Zita , Hellinger Roland , Broeck Jozef Vanden , Oetjen Janina , Liebeke Manuel , Gruber Christian W. 
Published: November 2022

AbstractNeuropeptides are important regulators of animal physiology and behavior. Hitherto large-scale localization of neuropeptides mainly relied on immunohistochemical methods requiring the availability of antibody panels, while another limiting factor has been the brain’s opacity for subsequent light or fluorescence microscopy. To address these limitations, we integrated high-resolution mass spectrometry imaging (MSI) with microtomography for a multiplexed mapping of neuropeptides in two evolutionary distant ant species,Atta sexdensandLasius niger. For analyzing the spatial distribution of chemically diverse peptide molecules across the brain in each species, the acquisition of serial mass spectrometry images was essential. As a result, we have comparatively mapped the 3D distributions of eight conserved neuropeptides throughout the brain micro-anatomy. We demonstrate that integrating the 3D MSI data into high-resolution anatomy models can be critical for studying organs with high plasticity such as brains of social insects. Several peptides, like the tachykinin-related peptides TK1 and TK4, were widely distributed in many brain areas of both ant species, whereas others, for instance myosuppressin was restricted to specific regions only. Also, we detected differences at the species level; many peptides were identified in the optic lobe ofL. niger, but only one peptide (ITG-like) was found in this region inA. sexdens. Our approach provides the basis for investigating fundamental neurobiological processes by visualizing the unbiased 3D neurochemistry in its complex anatomic environment.Significance statementUntil recently, the inability to detect entire molecules such as neuropeptides within their spatial biological context and simultaneously link their occurrence to anatomically and physiologically relevant areas has limited our understanding of complex neurochemical processes. This situation has now changed dramatically with the optimization of a new multiplexed imaging method based on mass spectrometry, which enables us to study previously invisible processes at the microscopic scale. With the marriage of mass spectrometry imaging and microtomography, we show that it has become possible to build high-resolution maps of neuropeptides in complex anatomical structures as small as ant brains. These maps, embedded in the 3D neuroanatomy, expand the understanding of the spatial organization of brain chemistry and provide a baseline for neurobiological and neurochemical studies.
OsPSTOLbut notTaPSTOLcan play a role in nutrient use efficiency and works through conserved pathways in both wheat and rice
Authors: Milner Matthew , Bowden Sarah , Craze Melanie , Wallington Emma J. 
Published: November 2022

AbstractThere is a large demand to reduce inputs for current crop production, particularly phosphate and nitrogen inputs which are the two most frequently added supplements to agricultural production. Gene characterization is often limited to the native species from which it was identified, but may offer benefits to other species. To understand ifOsPSTOL, a gene identified from rice which improves tolerance to low P growth conditions, might improve performance and provide the same benefit in wheat,OsPSTOLwas transformed into wheat and expressed from a constitutive promoter. The ability ofOsPSTOLto improve nutrient acquisition under low phosphate or low nitrogen was evaluated. Here we show thatOsPSTOLworks through a conserved pathway in wheat and rice to improve yields under both low phosphate and low nitrogen. This increase is yield is mainly driven by improved uptake from the soil driving increased biomass and ultimately increased seed number, but does not change the concentration of N in the straw or grain. Overexpression ofOsPSTOLin wheat modifies N regulated genes to aid in this uptake whereas the putative homologTaPSTOLdoes not suggesting that expression ofOsPSTOLin wheat can help to improve yields under low input agriculture.