bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time-Domain Diffuse Optical Tomography for Precision Neuroscience
Authors: Chekin Yaroslav , Decker Dakota , Dehghani Hamid , Dubois Julien , Field Ryan M. , Gopalakrishnan Viswanath , Koch Erin M. , Lerner Gabriel , Aghajan Zahra M. , Miller Naomi , Olvera Isai , Patel Milin J. , Perdue Katherine L. , Schmidt Joshua , Szczepanski Victor 
Published: May 2024

AbstractRecent years have witnessed a rise in research utilizing neuroimaging for precision neuromedicine, but clinical translation has been hindered by scalability and cost. Time Domain functional Near Infrared Spectroscopy (TD-fNIRS), the gold standard of optical neuroimaging techniques, offers a unique opportunity in this domain since it provides superior depth sensitivity and enables resolution of absolute properties unlike its continuous wave counterparts. However, current TD systems have limited commercial availability, slow sampling rates, and sparse head coverage. Our team has overcome the technical challenges involved in developing a whole-head time-domain diffuse optical tomography (TD-DOT) system. Here, we present the system characterization results using standardized protocols and compare them to the state-of-the-art. Furthermore, we showcase the system performance in retrieving cortical activation maps during standard hemodynamic, sensory, and motor tasks. A combination of the system performance, signal quality, and ease-of-use can enable future studies aimed at investigating TD-DOT clinical applications.
Local and global density have distinct and parasite-dependent effects on infection in wild sheep
Authors: Albery Gregory F , Sweeny Amy R , Corripio-Miyar Yolanda , Evans Michael J , Hayward Adam , Pemberton Josephine M , Pilkington Jill G , Nussey Daniel H 
Published: May 2024

AbstractHigh density should drive greater parasite exposure. However, evidence linking density with infection generally uses density proxies, rather than of individuals per space within a continuous population.We used a long-term study of wild sheep to link within-population spatiotemporal variation in host density with individual parasite counts. Although four parasites exhibited strong positive relationships with local density, these relationships were mostly restricted to juveniles and faded in adults. Further, one ectoparasite showed strong negative relationships across all age classes. In contrast, population size – a measure of global density – had limited explanatory power, and its effects did not remove those of spatial density, but were complementary. These results indicate that local and global density can exhibit diverse and contrasting effects on infection within populations. Spatial measures of within-population local density may provide substantial additional insight to temporal metrics based on population size, and investigating them more widely could be highly revealing.
Deciduous forests hold conservation value for birds within South Andaman Island, India
Authors: Jayanth Arpitha , Patel Zankhna , Mubeen Mohammed , Karthikayan M , Naniwadekar Rohit 
Published: May 2024

ABSTRACTGreater diversity of habitats on islands is often correlated with higher species richness (including endemic and threatened taxa), implying the need to understand species-habitat associations. Such habitat associations would also point towards the role of abiotic filtering and competition in structuring species communities, necessitating the examination of the role of species traits and phylogenetic relationships in intra-island community organisation, an aspect poorly examined in literature. We investigated the composition and structuring of forest bird communities in closely co-occurring evergreen and deciduous forests within South Andaman Island (Indian Ocean), wherein the importance of deciduous forests for birds is undervalued. We sampled 27 transects over two years and compared bird species composition and diversity across the two habitats. We examined species-specific associations with habitat (forest) type, basal area, and distance from human settlements, and tested if these responses were explained by species functional traits and tested for phylogenetic niche conservatism after factoring the effects of environmental predictors. Bird species compositions were markedly distinct across the two habitat types, with deciduous forests having greater taxonomic, but not functional or phylogenetic, diversity of forest birds. The distribution of forest birds, including several endemic and threatened species within the island was largely explained by habitat type (with 39% of the bird species analysed showing higher occurrence probabilities in deciduous forests), followed by distance from human settlements and basal area. We did not find evidence of species traits or phylogenetic relationships mediating these habitat preferences, perhaps due to a relatively impoverished species pool, as is typical on islands. Nevertheless, our results underscore the value of deciduous forests in harbouring high islandic species diversity, and being the preferred habitat of several endemic and threatened bird species. Given the historic focus on evergreen forests and the increasing anthropogenic pressure on the forests of the Andamans, we highlight the critical need to include the rapidly diminishing deciduous forests in existing conservation plans.
Use of human AML cells to study graft-versus-leukemia immunity in xenogeneic mouse models of GVHD
Authors: Faville Charline , Silva Bianca E , Baron Frédéric , Ehx Grégory 
Published: May 2024

AbstractAllogeneic hematopoietic cell transplantation (allo-HCT) is the main therapeutic approach for patients with high-risk acute myeloid leukemia (AML), but the rate of relapse remains high and is associated with poor outcomes. Discovering new approaches to maximize the graft-versus-leukemia (GVL) effects while mitigating graft-versus-host disease (GVHD) should therefore be pursued. Because of the difficulties in modeling AML in mice, patient-derived xenotransplantations (PDX) in immunodeficient NSG mice are preferred to study the GVL effects. In PDX, AML is typically induced through the intravenous injection of cell lines or leukemic blasts obtained from patients. GVHD and GVL effects are induced by (co)-injecting human T cells or peripheral blood mononuclear cells (PBMCs). While this approach enables the induction of systemic leukemia, notably developing in the spleen and bone marrow of the animals, it can also be associated with difficulties in monitoring the disease, notably by flow cytometry. This can be circumvented by using luciferase-expressing AML cells or transplanting the leukemic cells in Matrigel to generate solid tumors that are easier to monitor. Here, we provide detailed instructions on how to prepare human PBMCs and leukemic cells, transplant them, and monitor the disease in NSG mice.
Partial Fitch Graphs: Characterization, Satisfiability and Complexity∗
Authors: Hellmuth Marc , Korchmaros Annachiara , Ramírez-Rafael José Antonio , Schmidt Bruno , Stadler Peter F. , Thekkumpadan Puthiyaveedu Sandhya 
Published: May 2024

AbstractHorizontal gene transfer is an important contributor to evolution. Following Walter M. Fitch, two genes are xenologs if at least one HGT separates them. More formally, the directed Fitch graph has a set of genes as its vertices, and directed edges (x, y) for all pairs of genesxandyfor whichyhas been horizontally transferred at least once since it diverged from the last common ancestor ofxandy. Subgraphs of Fitch graphs can be inferred by comparative sequence analysis. In many cases, however, only partial knowledge about the “full” Fitch graph can be obtained. Here, we characterize Fitch-satisfiable graphs that can be extended to a biologically feasible “full” Fitch graph and derive a simple polynomial-time recognition algorithm. We then proceed to show that several versions of finding the Fitch graph with total maximum (confidence) edge-weights are NP-hard. In addition, we provide a greedy-heuristic for “optimally” recovering Fitch graphs from partial ones. Somewhat surprisingly, even if ∼ 80% of information of the underlying input Fitch-graphGis lost (i.e., the partial Fitch graph contains only ∼ 20% of the edges ofG), it is possible to recover ∼ 90% of the original edges ofGon average.
Quantitative cancer-immunity cycle modeling for predicting disease progression in advanced metastatic colorectal cancer
Authors: Li Chenghang , Wei Yongchang , Lei Jinzhi 
Published: May 2024

AbstractPatients diagnosed with advanced metastatic colorectal cancer (mCRC) often exhibit heterogeneous disease progression and face poor survival prospects. In order to comprehensively analyze the varied treatment responses among individuals and the challenge of tumor recurrence resistant to drugs in advanced mRCR, we developed a novel quantitative cancer-immunity cycle (QCIC) model. The proposed model was meticulously crafted utilizing a blend of differential equations and randomized modeling techniques to quantitatively elucidate the intricate mechanisms governing the cancer-immunity cycle and forecast tumor dynamics under different treatment modalities. Furthermore, by integrating diverse clinical datasets and rigorous model analyses, we introduced two pivotal concepts: the treatment response index (TRI) and the death probability function (DPF). These concepts are crucial tools for translating model predictions into clinically relevant evaluation indexes. Using virtual patient technology, we extrapolated tumor predictive biomarkers from the model to predict survival outcomes for mCRC patients. Our findings underscore the significance of tumor-infiltrating CD8+CTL cell density as a key predictive biomarker for short-term treatment responses in advanced mCRC while emphasizing the potential predict value of the tumor-infiltrating CD4+Th1/Treg ratio in determining patient survival. This study presents a pioneering methodology bridging the divide between diverse clinical data sources and the generation of virtual patients, offering invaluable insights into understanding inter-individual treatment variations and forecasting survival outcomes in mCRC patients.Author summaryThis study introduces a sophisticated modeling approach to delineate the intricate dynamics of tumor-immune interactions within the cancer-immunity cycle. Utilizing a multi-compartmental, multi-scale, multi-dimensional differential equation model, we quantified the complex interplay between tumor cells, immune cells, cytokines, and chemokines. By integrating virtual patient technology, we have conductedin silicoclinical trials that accurately predict disease progression across multiple treatment modalities for cancer patients, particularly in advanced mCRC. Through the combination of differential equations and randomized modeling, we effectively captured the diverse treatment responses and clinical manifestations of drug-resistant tumor recurrence. Furthermore, we explored the pivotal role of predictive biomarkers in determining patients’ survival prognosis, offering insights for tailored therapeutic strategies. Importantly, our computational framework holds promise for the extension to the investigation of patients with other tumor types, thus contributing to the personalized investigation of patients with other tumor types and cancer care.
Supervised Machine Learning for Bioelectrical Cellular Networks
Authors: Jaundoo Rajeev , Craddock Travis J.A. , Tuszynski Jack A. 
Published: May 2024

1.AbstractCells utilize bioelectricity to form networks as well as regulate and control a variety of processes such as apoptosis, tumor suppression, and voltage-gated ion channels. In-silico modeling of bioelectrical networks can be performed using BETSE, an application that models gap junctions and ion channel activity of networked cells, but its usage of matrix-based differential equations to estimate these properties limits simulations based on the amount of computational resources available. To alleviate this issue, we trained a total of 8 machine learning models to replace three core functions of BETSE, that is, 1) predicting the average transmembrane potential (Vmem) of an entire cellular network, 2) predicting the Vmemof each individual cell within the network, and finally, 3) predicting the average ion concentrations of sodium, potassium, chloride, and calcium within the cell network. For objective 1, the random forest model was shown to be most performant over all 4 scoring metrics, in objective 2 both the decision tree and k-nearest neighbors models scored best in half of all metrics, and for objective 3 the super learner, a meta-learner comprised of multiple base learners, scored best among all scoring metrics. Overall, these models provide a more resource efficient method of predicting properties of bioelectric cellular networks, and future work will include further properties such as temperature and pressure.
Virectaria stellata(Sabiceeae-Rubiaceae), a new sandstone cliff species from the Republic of Guinea with stellate hairs recorded for the first time in the Rubiaceae
Authors: Simbiano Faya Julien , Van Der Burgt Xander M. , Darbyshire Iain , Haba Pepe M. , Konomou Gbamon , Cheek Martin , Couch Charlotte , Magassouba Sékou 
Published: May 2024

AbstractVirectariais a morphologically isolated genus of tropical African herbs or subshrubs, occurring from Senegal to Tanzania.Virectaria stellata, a new species from Guinea, is published. It is a perennial herb, with stems becoming creeping and rooting, to 60 cm long.Virectaria stellatahas stellate hairs, recorded here for the first time in the family Rubiaceae. We hypothesize that the stellate hairs of this species result from horizontal gene flow from an Acanthaceae, most likelyBarleria, due to their common and perhaps unique microstructure.Virectaria stellatais found in Forécariah and Kindia Prefectures in the Republic of Guinea. The species occurs in fissures in vertical sandstone rock at altitudes of 450 to 910 m, in sun or half-shade. An overview of sandstone endemic plant species in the vicinity of the newVirectariais provided. No threats have been observed, therefore,Virectaria stellatais provisionally assessed here as Least Concern (LC).
GIBBERELLIN SIGNALING THROUGH RGA SUPPRESSES GCN5 EFFECT ON STAMEN ELONGATION OF ARABIDOPSIS FLOWERS
Authors: Balouri Christina , Poulios Stylianos , Tsompani Dimitra , Spyropoulou Zoe , Ketikoglou Maria-Christina , Kaldis Athanasios , Doonan John H , Vlachonasios Konstantinos E 
Published: May 2024

AbstractHistone acetyltransferases (HAT) modify the amino-terminal tails of the core histone proteins via acetylation, regulating chromatin structure and transcription. The GENERAL CONTROL NON-DEREPRESSIBLE 5 (GCN5) is a HAT that specifically acetylates H3K14 residues. GCN5 has been associated with cell division and differentiation, meristem function, root, stem, foliar and floral development, and plant environmental response. The flowers ofgcn5–6plants display reduced length of stamen and exhibit male sterility relative to the wild-type plants. We show these effects may arise from gibberellin (GA) signaling defects. The signaling pathway of bioactive GAs depends on the proteolysis of their repressors, DELLA proteins. The DELLA protein, REPRESSOR OF GA (RGA), represses plant growth, inflorescence, flower and seed development. Our molecular data indicate that GCN5 is required for activation and H3K14 acetylation of genes involved in the late stages of GA biosynthesis and catabolism. We studied the genetic interaction of RGA and GCN5; RGA can partially suppress GCN5 action. The reduced elongation of the stamen filament ofgcn5–6mutants is reversed in therga–t2;gcn5–6double mutants. This mechanism involved suppressing the GCN5 effect on the expression and histone acetylation inGAI-locus by RGA. Interestingly, RGA and RGL2 do not suppress ADA2b function, suggesting that ADA2b acts downstream in GA signaling and is distinct from GCN5 activity. In conclusion, we propose that the action of GCN5 on stamen elongation is mediated partially by RGA and GA signaling.
Two major-effect loci influence assortative mating in females of the sibling species,Drosophila simulansandD. sechellia
Authors: Lu Kenneth , Erezyilmaz Deniz 
Published: May 2024

AbstractSecondary contact between incompletely isolated species can produce a wide variety of outcomes, including production of new species and adaptive radiations. The vinegar fliesDrosophila simulansandD. sechelliadiverged on islands in the Indian Ocean and are currently separated by partial pre– and postzygotic barriers. The recent discovery of hybridization betweenD. simulansandD. sechelliain the wild presents an opportunity to monitor the prevalence of alleles that influence introgression between these species. We therefore sought to identify those loci that affect assortative mating, and we adapted a two-choice assay to test behavioral isolation in females. Using high-resolution seq-based QTL mapping, we found two major effect loci on the third chromosome that have a profound effect upon assortative mating of females. Each major QTL accounts for 32-37% of the difference in phenotype on its own, which is highly significant for a behavioral trait. The two major QTL of both backcrosses co-localize in one-dimensional analyses, suggesting that they may be alternate alleles of the same loci. The major-effect loci also co-localize with genes that encode enzymes required for female– and species-specific production of the pheromone, 7,11-heptacosadiene, emphasizing the importance of female attractiveness to males in separation of these species. Moreover, the genetic architecture of female assortative mating may be a factor in species separation, since alleles that influence assortative mating in females are linked to major-effect loci that influence assortative mating in males, and to loci that contribute to host fruit adaptation inD. sechellia.
Adaptive Differentiation in the General-Purpose Genotype Invasive PlantErythranthe guttata
Authors: Millar Aaron O , Chapman Hazel M 
Published: May 2024

AbstractHighly plastic general-purpose genotypes are a frequent occurrence among invasive plants. Yet, it remains uncertain to what extent genetic adaptation can co-occur with such elevated levels of plasticity. Understanding the interplay between these two evolutionary strategies is essential to better predict invasive success and future climate change responses.We investigated the potential for local adaptation along an altitudinal gradient in introduced New Zealand populations of the highly plastic invasive herb,Erythranthe guttata. We asked a) whether there were phenotypic differences between upland and lowlandE. guttatapopulations along our gradient; b) whether any differences were consistent with known adaptive patterns; and c) whether any adaptive patterns exist alongside high plasticity to elevation.Samples from 38E. guttatapopulations from upland and lowland Canterbury were grown from cuttings in a lowland and an upland common garden, where we measured a broad range of growth and reproductive traits.We found significant adaptive differentiation between upland and lowland populations over almost all measured traits. Upland populations had earlier and more intense flowering compared with lowland populations. Lowland plants were taller and had larger leaves with higher photosynthetic rates than upland plants. These differences occurred alongside high levels of unspecialised plasticity to the growing environment.Synthesis: We found that over a period of less than 150 years the environment along an altitude gradient of 120km has selected for distinct lowland and upland phenotypes ofE. guttata. These changes reflect common selective pressure associated with altitude gradients, increasing reproductive success at higher altitudes and increased competitive ability at lower altitudes. This rapid local adaptation occurred alongside high plasticity within the growing environment, showing that highly plastic invasive species still retain the capacity to genetically adapt to novel environments.
Effective target genes for RNA interference-based management of the cabbage stem flea beetle
Authors: Cedden Doga , Güney Gözde , Debaisieux Xavier , Scholten Stefan , Rostás Michael , Bucher Gregor 
Published: May 2024

AbstractThe cabbage stem flea beetle (CSFB,Psylliodes chrysocephala) is a key pest of oilseed rape. The ban on neonicotinoids in the European Union due to environmental concerns and the emergence of pyrethroid-resistant populations have made the control of CSFB extremely challenging. In search of a solution, we have recently shown that RNA interference (RNAi) has potential in the management of CSFB. However, the previously tested target genes for RNAi-mediated pest control (subsequently calledtarget genes) exhibited moderate and slow-acting lethal effects. In this study, 27 double-stranded RNAs (dsRNAs) were orally delivered to identify highly effective target genes in CSFB adults by leveraging the findings of a genome-wide RNAi screen inTribolium castaneum. Our screen using 500 ng of dsRNA identified 10 moderately effective (> 50% mortality) and 4 highly effective target genes (100% mortality in 8-13 days). The latter mainly included proteasome subunits. RT-qPCR experiments confirmed target gene silencing and dose-response studies revealed LD50values as low as ∼20 ng in 14 days following a single exposure to dsRNA. Four highly effective dsRNAs also inhibited leaf damage (up to ∼75%) and one affected locomotion. The sequences of promising target genes were subjected toin silicotarget prediction in non-target organisms, e.g., beneficials such as honeybees, to design environmentally friendly dsRNAs. Overall, the study provides valuable insights for the development of dsRNA-based insecticides against CSFB.