bluuebunny/crossref_metadata_2025_split huggingface dataset:
The grass that built the Central Highland of Madagascar: environmental niches and morphological diversity ofLoudetia simplex
Authors: Almary Tchana O. M. , White Joseph , Rasaminirina Fitiavana , Razanatsoa Jacqueline , Lehmann Caroline , Rakotoarinivo Mijoro , Ralimanana Hélène , Vorontsova Maria S. , Tiley George P. 
Published: September 2023

SUMMARY1) Research Aims —Loudetia simplexis a common and dominant species throughout grassland ecosystems in mainland Africa and Madagascar. It is highly polymorphic, often classified as two taxa endemic to Madagascar:L. simplexsubsp.stipoidesandL. madagascariensis. A better understanding of the inter- and intra-specific variation between these taxa and its contributing environmental factors could improve our understanding of the history of Madagascar’s grasslands.2) Methods — The taxonomic status ofL. simplexsubsp.stipoidesandL. madagascariensiswas evaluated by morphometric analyses of 119 herbarium specimens. Species distribution modelling was used to determine the most important environmental factors underlyingthe L. simplexdistribution in Madagascar versus other African grasslands. We investigated ifL. simplexin Madagascar could be predicted by distributions across mainland Africa with niche overlap analyses.3) Key Result — African and Malagasy species exhibited variation potentially associated with environment. Specimens from northern and western Madagascar were taller with smaller spikelets than those from Southern Africa and central Madagascar.Loudetia simplextypically occurred in cooler temperatures with high precipitation and pronounced seasonality, but taller populations were found in warmer conditions. Projecting ecological niches of Southern Africa and East Tropical Africa onto Madagascar demonstrates much of the present distribution in the Central Highlands is expected from other natural African grasslands.4) Key Point — Malagasy and African individuals represent a single species, and the Malagasy species can be considered as a synonym of L. simplex. Distribution models are congruent with pre-human presence of grasslands in Madagascar.SOCIETAL IMPACT STATEMENTUnderstanding dominant species likeLoudetia simplexis necessary to understand the fire-driven grassy ecosystems they create. In Madagascar, grasslands are considered a low-value ecosystem despite their unique biodiversity and crucial importance as zebu rangeland. Only 1.8% of Madagascar’s grasslands are protected despite facing similar threats to forests and biodiversity loss. This study of common grasses will support the management of protected areas by providing information on resource management of vulnerable open ecosystems in Madagascar. Distribution models of common grass species and clear taxonomic classification can help land management stakeholders identify natural grasslands versus degraded forests.
lista-GEM: the genome-scale metabolic reconstruction ofLipomyces starkeyi
Authors: Almeida Eduardo , Ferreira Mauricio , Silveira Wendel 
Published: September 2023

AbstractOleaginous yeasts cultivation in low-cost substrates is an alternative for more sustainable production of lipids and oleochemicals.Lipomyces starkeyiaccumulates high amounts of lipids from different carbon sources, such as glycerol, and glucose and xylose (lignocellulosic sugars). Systems metabolic engineering approaches can further enhance its capabilities for lipid production, but no genome-scale metabolic networks have been reconstructed and curated forL. starkeyi. Herein, we proposelista-GEM, the first genome-scale metabolic model ofL. starkeyi. We reconstructed the model using two high-quality models of oleaginous yeasts as templates and further curated the model to reflect the metabolism ofL. starkeyi. We simulated phenotypes and predicted flux distributions in good accordance with experimental data. We also predicted targets to improve lipid production in glucose, xylose, and glycerol. The phase plane analysis indicated that the carbon availability affected lipid production more than oxygen availability. We found that the maximum lipid production in glucose and xylose required more oxygen than glycerol. Enzymes related to lipid synthesis in the endoplasmic reticulum were the main targets to improve lipid production: stearoyl-CoA desaturase, fatty-acyl-CoA synthase, diacylglycerol acyltransferase, and glycerol-3-phosphate acyltransferase. The glycolytic genes encoding pyruvate kinase, enolase, phosphoglycerate mutase, glyceraldehyde-3-phosphate dehydrogenase, and phosphoglycerate kinase were predicted as targets for overexpression. Pyruvate decarboxylase, acetaldehyde dehydrogenase, acetyl-CoA synthetase, adenylate kinase, inorganic diphosphatase, and triose-phosphate isomerase were predicted only when glycerol was the carbon source. Therefore, we demonstrated thatlista-GEM provides multiple metabolic engineering targets to improve lipid production byL. starkeyiusing carbon sources from agricultural and industrial wastes.HighlightsLipomyces starkeyican accumulate high amounts of lipids from carbon sources found in agricultural and industrial wastes.We reconstructedlista-GEM, the first genome-scale metabolic model ofL. starkeyi.Simulated phenotypes were in line with experimental results ofL. starkeyi.We identified key gene targets for improving lipid production using metabolic engineering.
Autophagy-dependent alternative splicing event produces a more stable ribosomal protein S24 isoform that aids in hypoxic cell survival
Authors: Kerry Jenna , Specker Erin J. , Mizzoni Morgan , Brumwell Andrea , Fell Leslie , Goodbrand Jenna , Rosen Michael N. , Uniacke James 
Published: September 2023

ABSTRACTOverlapping or convergent stress-activated molecular pathways exist to coordinate cell fate in response to stimuli such as hypoxia, oxidative stress, DNA damage, and unfolded proteins. Cells can remodel the splicing and translation machineries to mount a specialized gene expression response to certain stresses. Here, we show that hypoxic human cells in 2D and 3D culture models increase the relative abundance by 1.7- to 2.6-fold and 4.7- to 11.5-fold, respectively, of a longer mRNA variant of ribosomal protein S24 (RPS24L) compared to a shorter mRNA variant (RPS24S) by favoring the inclusion of a 22 bp cassette exon. Mechanistically, RPS24L and RPS24S are induced and repressed, respectively, by distinct parallel pathways in hypoxia: RPS24L is induced in an autophagy-dependent manner, while RPS24S is reduced by mTORC1 repression and in a HIF-dependent manner. RPS24L is a more stable mRNA in hypoxia and produces a more stable protein isoform compared to RPS24S. Cells overexpressing RPS24L display improved survival and growth in hypoxia relative to control cells and cells overexpressing RPS24S, which display impaired survival. Previous work from our group showed a correlation between RPS24L levels and tumor hypoxia in prostate cancer. These data highlight RPS24L as a stress-induced alternative splicing event that favors hypoxic cell survival, which could be exploited by cancer cells in the tumor microenvironment.
Genetic variability in pathways associates with pesticide-induced nervous system disease in the United States
Authors: Kosnik Marissa B. , Antczak Philipp , Fantke Peter 
Published: September 2023

AbstractNervous system disease development following pesticide exposure can vary in a population, but genetic susceptibility to chemicals is poorly characterized. We developed a framework to build Chemical – SNP (single nucleotide polymorphism) – Disease linkages via biological pathways. We integrated these linkages with spatialized pesticide application data for the United States from 1992 – 2018 and nervous system disease rates for 2018 to characterize genetic variability in pesticide-induced nervous system disease. We found that the number of SNPs implicated per pesticide in US states positively correlates with disease incidence and prevalence for Alzheimer’s disease, Parkinson disease, and multiple sclerosis. Further, only 2% of pesticide sets used together over time overlapped between high disease occurrence and low disease occurrence states, with more SNPs implicated in pathways in high disease occurrence states. This supports that pesticides contribute to nervous system disease, and we developed priority lists of SNPs, pesticides, and pathways for further study.
TRIP13 localizes to synapsed chromosomes and functions as a dosage-sensitive regulator of meiosis
Authors: Chotiner Jessica Y. , Leu N. Adrian , Yang Fang , Cossu Isabella G. , Guan Yongjuan , Lin Huijuan , Wang P. Jeremy 
Published: September 2023

AbstractMeiotic progression requires coordinated assembly and disassembly of protein complexes involved in chromosome synapsis and meiotic recombination. The AAA+ ATPase TRIP13 and its orthologue Pch2 are instrumental in remodeling HORMA domain proteins. Meiosis-specific HORMAD proteins are associated with unsynapsed chromosome axes but depleted from the synaptonemal complex (SC) of synapsed chromosome homologues. Here we report that TRIP13 localizes to the synapsed SC in early pachytene spermatocytes and to telomeres throughout meiotic prophase I. Loss of TRIP13 leads to meiotic arrest and thus sterility in both sexes.Trip13-null meiocytes exhibit abnormal persistence of HORMAD1 and HOMRAD2 on synapsed SC and chromosome asynapsis that preferentially affects XY and centromeric ends. These findings confirm the previously reported phenotypes of theTrip13hypomorph alleles.Trip13heterozygous (Trip13+/-) mice also exhibit meiotic defects that are less severe than theTrip13-null mice, showing that TRIP13 is a dosage-sensitive regulator of meiosis. Localization of TRIP13 to the synapsed SC is independent of SC axial element proteins such as REC8 and SYCP2/SYCP3. The N- or C-terminal FLAG-tagged TRIP13 proteins are functional and recapitulate the localization of native TRIP13 to SC and telomeres in knockin mice. Therefore, the evolutionarily conserved localization of TRIP13/Pch2 to the synapsed chromosomes provides an explanation for dissociation of HORMA domain proteins upon chromosome synapsis in diverse organisms.
Modeling Cardiomyocyte Signaling and Metabolism Predicts Genotype to Phenotype Mechanisms in Hypertrophic Cardiomyopathy
Authors: Khalilimeybodi A. , Saucerman Jeffrey J. , Rangamani P. 
Published: September 2023

AbstractFamilial hypertrophic cardiomyopathy (HCM) is a significant precursor of heart failure and sudden cardiac death, primarily caused by mutations in sarcomeric and structural proteins. Despite the extensive research on the HCM genotype, the complex, context-specific nature of many signaling and metabolic pathways linking the HCM genotype to phenotype has hindered therapeutic advancements for patients. To address these challenges, here, we have developed a computational systems biology model of HCM at the cardiomyocyte level. Utilizing a stochastic logic-based ODE method, we integrate subcellular systems in cardiomyocytes that jointly modulate HCM genotype to phenotype, including cardiac signaling, metabolic, and gene regulatory networks, as well as posttranslational modifications linking these networks. After validating with experimental data on changes in activity of signaling species in HCM context and transcriptomes of two HCM mouse models (R403Q-αMyHC and R92W-TnT), the model predicts significant changes in cardiomyocyte metabolic functions such as ATP synthase deficiency and a transition from fatty acids to carbohydrate metabolism in HCM. The model indicated major shifts in glutamine-related metabolism and increased apoptosis after HCM-induced ATP synthase deficiency. Aligned with prior experimental studies, we predicted that the transcription factors STAT, SRF, GATA4, TP53, and FoxO are the key regulators of cardiomyocyte hypertrophy and apoptosis in HCM. Using the model, we identified shared (e.g., activation of PGC1αby AMPK, and FHL1 by titin) and context-specific mechanisms (e.g., regulation of Ca2+sensitivity by titin in HCM patients) that could control genotype to phenotype transition in HCM across different species or mutations. We also predicted potential combination drug targets for HCM (e.g., mavacamten paired with ROS inhibitors) preventing or reversing HCM phenotype (i.e., hypertrophic growth, apoptosis, and metabolic remodeling) in cardiomyocytes. This study provides new insights into mechanisms linking genotype to phenotype in familial hypertrophic cardiomyopathy and offers a framework for assessing new treatments and exploring variations in HCM experimental models.
Ventral CA1 Population Codes for Anxiety
Authors: Lim Sean C. , Fusi Stefano , Hen René 
Published: September 2023

SUMMARYThe ventral hippocampus is a critical node in the distributed brain network that controls anxiety. Using miniature microscopy and calcium imaging, we recorded ventral CA1 (vCA1) neurons in freely moving mice as they explored variants of classic behavioral assays for anxiety. Unsupervised behavioral segmentation revealed clusters of behavioral motifs that corresponded to exploratory and vigilance-like states. We discovered multiple vCA1 population codes that represented the anxiogenic features of the environment, such as bright light and openness, as well as the moment-to-moment anxiety state of the animals. These population codes possessed distinct generalization properties: neural representations of anxiogenic features were different for open field and elevated plus/zero maze tasks, while neural representations of moment-to-moment anxiety state were similar across both experimental contexts. Our results suggest that anxiety is not tied to the aversive compartments of these mazes but is rather defined by a behavioral state and its corresponding population code that generalizes across environments.
Do we still need Illumina sequencing data?: Evaluating Oxford Nanopore Technologies R10.4.1 flow cells and v14 library prep kits for Gram negative bacteria whole genome assemblies
Authors: Lerminiaux Nicole , Fakharuddin Ken , Mulvey Michael R. , Mataseje Laura 
Published: September 2023

AbstractThe best whole genome assemblies are currently built from a combination of highly accurate short-read sequencing data and long-read sequencing data that can bridge repetitive and problematic regions. Oxford Nanopore Technologies (ONT) produce long-read sequencing platforms and they are continually improving their technology to obtain higher-quality read data that is approaching the quality obtained from short-read platforms such as Illumina. As these innovations continue, we were interested in evaluating how much ONT read coverage produced by the Rapid Barcoding Kit v14 (SQK-RBK114) is necessary to generate high-quality hybrid and long-read-only genome assemblies for a panel of carbapenemase-producingEnterobacteralesbacterial isolates. We found that 30X long-read coverage is sufficient if Illumina data is available, and that 100X long-read coverage is recommended for long-read-only assemblies. We found that Illumina polishing is still improving SNVs and INDELs in long-read-only assemblies. We also examined if antimicrobial resistance genes could be accurately identified in long-read-only data, and found that Flye assemblies regardless of ONT coverage detected > 94 % of resistance genes at 100% identity and length. Overall, the Rapid Barcoding Kit v14 and long-read-only assemblies can be an optimal sequencing strategy depending on the specific use case and resources available.
The ghost of selection past: evolution and conservation relevance of the kākāpō color polymorphism
Authors: Urban Lara , Santure Anna W. , Uddstrom Lydia , Digby Andrew , Vercoe Deidre , Eason Daryl , Crane Jodie ,   Kākāpō Recovery Team, Wylie Matthew J. , Davis Tāne , LeLec Marissa F. , Guhlin Joseph , Poulton Simon , Slate Jon , Alexander Alana , Fuentes-Cross Patricia , Dearden Peter K. , Gemmell Neil J. , Azeem Farhan , Weyland Marvin , Schwefel Harald G. L. , van Oosterhout Cock , Morales Hernán E. 
Published: September 2023

AbstractThe information contained in population genomic data can tell us much about the past ecology and evolution of species. We leveraged detailed phenotypic and genomic data of nearly all living kākāpō to understand the evolution of its remarkable feather color polymorphism. The kākāpō is an endangered and culturally significant parrot endemic to Aotearoa New Zealand, and the green and olive feather colorations are present at similar frequencies in the population. The presence of such a neatly balanced color polymorphism is remarkable because the entire population currently numbers less than 250 birds, which means it has been exposed to severe genetic drift. We dissected the color phenotype, demonstrating that the two colors differ in their light reflectance patterns due to differential feather structure. We used quantitative genomics methods to identify two genetic variants whose epistatic interaction can fully explain the species’ color phenotype. Our genomic forward simulations show that balancing selection might have been pivotal to establish the polymorphism in the ancestrally large population, and to maintain it during population declines that involved a severe bottleneck. We hypothesize that an extinct apex predator was the likely agent of balancing selection, making the color polymorphism in the kākāpō a “ghost of selection past”.
The genomic landscape of metallic color variation in ground beetles
Authors: Weng Yi-Ming , Kavanaugh David H. , Rubio-Perez Bryan , Salman Jad , Kats Mikhail A. , Schoville Sean D. 
Published: September 2023

AbstractThe metallic color variation of beetles is a spectacular feature that has inspired diverse human cultures. However, little is known about the genetic basis of this trait or its ecological importance. In this study, we characterize the geographical distribution, optical mechanism, genetic basis, and ecological and evolutionary importance of metallic color variation in theNebria ingenscomplex, an alpine ground beetle in the Sierra Nevada, California. We find that elytral color varies continuously across two allopatric species (from blackN. ingensto greenN. riversi), with hybrid populations showing intermediate coloration, and we demonstrate that the metallic color is generated from multilayer reflectors in the epicuticle of the elytra. By applying association mapping in natural populations (wild-GWAS) using high-density SNPs (1.2 million), we identify five promising candidate genes covarying with metallic variation, with known roles in cuticle formation and pigmentation pathways. Among these five genes, the geneyellow-like exhibits a heightened divergence pattern relative to the background genomic landscape and has been maintained despite gene flow. This finding, together with a significant correlation between color variation and water availability, suggests that metallic variation evolves as a local adaptation to environmental variation in theN. ingenscomplex.
Fluorescent Tools for Imaging and Ligand Screening of Dopamine D2-Like Receptors
Authors: Nagl Martin , Mönnich Denise , Rosier Niklas , Schihada Hannes , Sirbu Alexei , Konar Nergis , Reyes-Resina Irene , Navarro Gemma , Franco Rafael , Kolb Peter , Annibale Paolo , Pockes Steffen 
Published: September 2023

AbstractThe family of dopamine D2-like receptors represent an interesting target for a variety of neurological diseases, e.g. Parkinson’s disease (PD), addiction or schizophrenia. In this study we describe the synthesis of a new set of fluorescent ligands as tools for visualization of dopamine D2-like receptors. Pharmacological characterization in radioligand binding studies identified UR-MN212 (20) as a high-affinity ligand for D2-like receptors (pKi(D2longR) = 8.24, pKi(D3R) = 8.58, pKi(D4R) = 7.78) with decent selectivity towards D1-like receptors. Compound20is a neutral antagonist in a Go1activation assay at the D2longR, D3R and D4R, which is an important feature for studies using whole cells. The neutral antagonist20, equipped with a 5-TAMRA dye, displayed rapid association to the D2longR in binding studies using confocal microscopy demonstrating its suitability for fluorescence microscopy. Furthermore, in molecular brightness studies, the ligand’s binding affinity could be determined in a single-digit nanomolar range that was in good agreement with radioligand binding data. Therefore, the fluorescent compound can be used for quantitative characterization of native D2-like receptors in a broad variety of experimental setups.
Study on the influence of different contents of impure CaO on the process of electromelting magnesia
Authors: Li Zhen , Qu Dian-li , Luo Xu-dong , Chen Na 
Published: September 2023

Purpose
The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

Design/methodology/approach
The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

Findings
The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

Originality/value
The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.
Detecting future financial statement fraud using a machine learning model in Indonesia: a comparative study
Authors: Riskiyadi Moh. 
Published: September 2023

PurposeThis study aims to compare machine learning models, datasets and splitting training-testing using data mining methods to detect financial statement fraud.Design/methodology/approachThis study uses a quantitative approach from secondary data on the financial reports of companies listed on the Indonesia Stock Exchange in the last ten years, from 2010 to 2019. Research variables use financial and non-financial variables. Indicators of financial statement fraud are determined based on notes or sanctions from regulators and financial statement restatements with special supervision.FindingsThe findings show that the Extremely Randomized Trees (ERT) model performs better than other machine learning models. The best original-sampling dataset compared to other dataset treatments. Training testing splitting 80:10 is the best compared to other training-testing splitting treatments. So the ERT model with an original-sampling dataset and 80:10 training-testing splitting are the most appropriate for detecting future financial statement fraud.Practical implicationsThis study can be used by regulators, investors, stakeholders and financial crime experts to add insight into better methods of detecting financial statement fraud.Originality/valueThis study proposes a machine learning model that has not been discussed in previous studies and performs comparisons to obtain the best financial statement fraud detection results. Practitioners and academics can use findings for further research development.