bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validating the representation of distance between infarct diseases using Word2Vec word embedding
Authors: Yokokawa Daiki , Noda Kazutaka , Yanagita Yasutaka , Uehara Takanori , Ohira Yoshiyuki , Shikino Kiyoshi , Tsukamoto Tomoko , Ikusaka Masatomi 
Published: June 2022

AbstractObjectiveTo determine if inter-disease distances between word embedding vectors using the picot-and-cluster strategy (PCS) are a valid quantitative representation of similar disease groups in a limited domain.Materials and MethodsAbstracts were extracted from the Ichushi-Web database and subjected to morphological analysis and training using the Word2Vec. From this, word embedding vectors were obtained. For words including “infarction”, we calculated the cophenetic correlation coefficient (CCC) as an internal validity measure and the adjusted rand index (ARI), normalized mutual information (NMI), and adjusted mutual information (AMI) with ICD-10 codes as the external validity measures. This was performed for each combination of metric and hierarchical clustering method.ResultsSeventy-one words included “infarction”, of which 38 diseases matched the ICD-10 standard with the appearance of 21 unique ICD-10 codes. The CCC was most significant at 0.8690 (metric and method: euclidean and centroid), while the AMI was maximal at 0.4109 (metric and method: cosine and correlation, and average and weighted). The NMI and ARI were maximal at 0.8463 and 0.3593, respectively (metric and method: cosine and complete).DiscussionThe metric and method that maximized the internal validity measure were different from those that maximized the external validity measures; both produced different results. The Cosine distance should be used when considering ICD-10, and the Euclidean distance when considering the frequency of word occurrence.ConclusionThe distributed representation, when trained by Word2Vec on the “infarction” domain from a Japanese academic corpus, provides an objective inter-disease distance used in PCS.
Co-occurrences enhance our understanding of aquatic fungal metacommunity assembly and reveal potential host–parasite interactions
Authors: Vass Máté , Eriksson Karolina , Carlsson-Graner Ulla , Wikner Johan , Andersson Agneta 
Published: June 2022

AbstractOur knowledge of aquatic fungal communities, their assembly, distributions and ecological roles in marine ecosystems is scarce. Hence, we aimed to investigate fungal metacommunities of coastal habitats in a subarctic zone (northern Baltic Sea, Sweden). Using a novel joint species distribution model and network approach, we quantified the importance of biotic associations contributing to the assembly of mycoplankton, further, detected potential biotic interactions between fungi–algae pairs, respectively. Our long-read metabarcoding approach identified 504 fungal taxa, of which a dominant fraction (44.8 %) was assigned as early-diverging fungi (i.e., Cryptomycota and Chytridiomycota). Alpha diversity of mycoplankton declined and community compositions changed along inlet–bay– offshore transects. The distributions of most fungi were rather influenced by spatial factors than by environmental drivers, and the influence of biotic associations was pronounced when environmental filtering was weak and spatial patterning lessened. We found great number of co-occurrences (138) among the dominant fungal groups, and the forty associations between fungal and algal OTUs suggested potential host–parasite/saprotroph links, supporting a Cryptomycota-based mycoloop pathway. We emphasize that the contribution of biotic associations to mycoplankton assembly are important to consider in future studies as it helps to improve predictions of species distributions in aquatic ecosystems.
Pancreatic tumors activate arginine biosynthesis to adapt to myeloid-driven amino acid stress
Authors: Apiz-Saab Juan J. , Dzierozynski Lindsey N. , Jonker Patrick B. , Zhu Zhou , Chen Riona N. , Oh Moses , Sheehan Colin , Macleod Kay F. , Weber Christopher R. , Muir Alexander 
Published: June 2022

AbstractNutrient stress in the tumor microenvironment requires cancer cells to adopt adaptive metabolic programs to maintain survival and proliferation. Therefore, knowledge of microenvironmental nutrient levels and how cancer cells cope with such nutrition is critical to understand the metabolism underpinning cancer cell biology. Previously, we performed quantitative metabolomics of the interstitial fluid (the local perfusate) of murine pancreatic ductal adenocarcinoma (PDAC) tumors to comprehensively characterize nutrient availability in the microenvironment of these tumors (Sullivan et al., 2019a). Here, we developTumorInterstitialFluidMedium (TIFM), a cell culture medium that contains nutrient levels representative of the PDAC microenvironment, enabling study of PDAC metabolism under physiological nutrition. We show that PDAC cells cultured in TIFM, compared to standard laboratory models, adopt a cellular state more similar to PDAC cells in tumors. Further, using the TIFM model we identified arginine biosynthesis as a metabolic adaptation PDAC cells engage to cope with microenvironmental arginine starvation driven by myeloid cells in PDAC tumors. Altogether, these data show that nutrient availability in tumors is an important determinant of cancer cell metabolism and behavior, and cell culture models that incorporate physiological nutrient availability have improved fidelity and enable the discovery of novel cancer metabolic phenotypes.
Octopamine affects gustatory responsiveness and associative learning performance in bumble bees
Authors: Muth Felicity , Breslow Emily , Leonard Anne S. 
Published: June 2022

AbstractOctopamine has broad roles within invertebrate nervous systems as a neurohormone, neurotransmitter and neuromodulator. It orchestrates foraging behavior in many insect taxa via effects on feeding, gustatory responsiveness and appetitive learning. Knowledge of how this biogenic amine regulates bee physiology and behavior is based largely on study of a single species, the honey bee,Apis mellifera. Until recently, its role in the foraging ecology and social organization of diverse bee taxa had been unexplored. Bumble bees (Bombusspp.) are a model for the study of foraging and learning, and its neural basis, but whether octopamine similarly affects sensory and cognitive performance in this genus is not known. To address this gap, we explored the effects of octopamine on sucrose response thresholds and associative learning inBombus impatiensvia conditioning of the Proboscis Extension Reflex (PER) using a visual (color) cue. We found that octopamine had similar effects on bumble bee behavior as honey bees, however, higher doses were required to induce these effects. At this higher dose, octopamine lowered bees’ sucrose response thresholds and appeared to enhance associative learning performance. Adding to recent studies on stingless bees (Meliponini), these findings support the idea that octopamine’s role in reward processing and learning is broadly conserved across Apidae, while pointing towards some differences across systems worth exploring further.
Adaptive, maladaptive, neutral, or absent plasticity: Hidden caveats of reaction norms
Authors: Eriksson Martin , Kinnby Alexandra , De Wit Pierre , Rafajlović Marina 
Published: June 2022

AbstractAdaptive phenotypic plasticity may improve the response of individuals when faced with new environmental conditions. Typically, empirical evidence for plasticity is based on phenotypic reaction norms obtained in reciprocal transplant experiments. In such experiments, individuals from their native environment are transplanted into a different environment, and a number of trait values, potentially implicated in individuals’ response to the new environment, are measured. However, the interpretations of reaction norms may differ depending on the nature of the assessed traits, which may not be known beforehand. For example, for traits that contribute to local adaptation, adaptive plasticity implies non-zero slopes of reaction norms. By contrast, for traits that are correlated to fitness, high tolerance to different environments (possibly due to adaptive plasticity in traits that contribute to adaptation) may, instead, result in flat reaction norms. Here we investigate reaction norms for adaptive versus fitness-correlated traits, and how they may affect the conclusions regarding the contribution of plasticity. To this end, we first simulate range expansion along an environmental gradient where plasticity evolves to different values locally and then perform reciprocal transplant experimentsin silico. We show that reaction norms alone cannot inform us whether the assessed trait exhibits locally adaptive, maladaptive, neutral or no plasticity, without any additional knowledge of the traits assessed and species’ biology. We use the insights from the model to analyse and interpret empirical data from reciprocal transplant experiments involving the marine isopodIdotea balthicasampled from two geographical locations with different salinities, concluding that the low-salinity population likely has reduced adaptive plasticity relative to the high-salinity population. Overall, we conclude that, when interpreting results from reciprocal transplant experiments, it is necessary to consider whether traits assessed are locally adaptive with respect to the environmental variable accounted for in the experiments, or correlated to fitness.
Electrophysiological characterization of medial preoptic neurons in lactating rats and its modulation by hypocretin-1
Authors: Rivas Mayda , Serantes Diego , Pascovich Claudia , Peña Florencia , Ferreira Annabel , Torterolo Pablo , Benedetto Luciana 
Published: June 2022

AbstractThe medial preoptic area (mPOA) undergoes through neuroanatomical changes across the postpartum period, during which its neurons play a critical role in the regulation of maternal behavior. In addition, this area is also crucial for sleep-wake regulation. We have previously shown that hypocretins (HCRT) within the mPOA facilitate active maternal behaviors in postpartum rats, while the blockade of endogenous HCRT in this area promotes nursing and sleep. To explore the mechanisms behind these HCRT actions, we aimed to evaluate the effects of juxta-cellular HCRT-1 administration on mPOA neurons in urethane-anesthetized postpartum and virgin female rats. We recorded mPOA single units and the electroencephalogram (EEG) and applied HCRT-1 juxta-cellular by pressure pulses. Our main results show that the electrophysiological characteristics of the mPOA neurons and their relationship with the EEG of postpartum rats did not differ from virgin rats. Additionally, neurons that respond to HCRT-1 had a slower firing rate than those that did not. In addition, administration of HCRT increased the activity in one group of neurons while decreasing it in another, both in postpartum and virgin rats. The mechanisms by which HCRT modulate functions controlled by the mPOA involve different cell populations.
Gender impacts the relationship between mood disorder symptoms and effortful avoidance performance
Authors: Forys Brandon J. , Tomm Ryan J. , Stamboliyska Dayana , Terpstra Alex R. , Clark Luke , Chakrabarty Trisha , Floresco Stan B. , Todd Rebecca M. 
Published: June 2022

AbstractWe must often decide how much effort to exert or withhold to avoid undesirable outcomes or obtain rewards. In depression and anxiety, levels of avoidance can be excessive and reward-seeking may be reduced. Yet outstanding questions remain about the links between motivated action/inhibition and anxiety and depression levels, and whether they differ between men and women. Here we examined the relationship between anxiety and depression scores, and performance on effortful active and inhibitory avoidance (Study 1) and reward seeking (Study 2) in humans. Undergraduates and paid online workers (NAvoid= 545,NReward= 310;NFemale= 368,NMale= 450,MAge= 22.58,RangeAge= 17-62) were assessed on the Beck Depression Inventory II (BDI) and the Beck Anxiety Inventory (BAI) and performed an instructed online avoidance or reward-seeking task. Participants had to make multiple presses on active trials and withhold presses on inhibitory trials to avoid an unpleasant sound (Study 1) or obtain points towards a monetary reward (Study 2). Overall, men deployed more effort than women in both avoidance and reward-seeking, and anxiety scores were negatively associated with active reward-seeking performance based on sensitivity scores. Gender interacted with anxiety scores and inhibitory avoidance performance, such that women with higher anxiety showed worse avoidance performance. Our results illuminate effects of gender in the relationship between anxiety and depression levels and the motivation to actively and effortfully respond to obtain positive and avoid negative outcomes.Significance statementWe must often take or withhold effortful action to avoid unpleasant outcomes or obtain rewards. Depression and anxiety can impact these behaviours’ effectiveness, but the roles of avoidance in depression and reward-seeking in anxiety are not fully understood. Gender differences in avoidance and reward-seeking have also not been examined. We present a task in which community participants with a range of anxiety and depression levels made or withheld button presses to avoid hearing an unpleasant sound or obtain a reward. Men deployed more effort than women in avoidance, and women with higher anxiety scores had lower avoidance performance than men. We illuminate gender differences in how depressive and anxiety scores impact our ability to avoid threats and obtain rewards.
Early exposure to high-fat diet impairs central and peripheral metabolic function: Impacts on cognition and mitochondrial function
Authors: Vilela Wembley Rodrigues , Bellozi Paula Maria Quaglio , Picolo Victor Luna , Cavadas Bruna Neves , Silva Marques Keila Valentina , Pereira Louise Tavares Garcia , Amato Angélica Amorim , Magalhães Kelly Grace , Mortari Márcia Renata , Goulart Jair Trapé , de Bem Andreza Fabro 
Published: June 2022

ABSTRACTThe impact of overnutrition early in life is not restricted to the onset of cardiovascular and metabolic diseases, but also affects critical brain functions related to cognition. This study aimed to evaluate the relationship between peripheral metabolic and bioenergetic changes induced by high-fat diet (HFD) and their impact on hippocampal cognitive functions in juvenile mice. To this purpose, three-week-old male C57BL/6 mice received a HFD or control diet for seven weeks, associated with two low doses of streptozotocin (STZ) or vehicle, to accelerate the metabolic dysfunction. HFD induced metabolic changes in mice, particularly related to glucose metabolism, in spite of the absence of obesity and changes in lipid profile. HFD exposure starting from weaning impaired recognition and spatial memories in mice, without inducing a depressive-like behavior. Increased immunoreactivity for GFAP and a trend towards a decrease in NeuN staining were verified in the hippocampus of HFD-fed mice. HFD caused a bioenergetic impairment in the hippocampus, characterized by a decrease in both O2 consumption related to ATP production and in the maximum respiratory capacity. The thermogenic capacity of brown adipose tissue was impaired by HFD, here verified through the absence of a decrease in O2 consumption after UCP-1 inhibition and increase in the reserve respiratory capacity. Impaired mitochondria function was also observed in the liver of HFD mice, while no changes were verified in O2 consumption in the heart of juvenile mice. These results indicate that the introduction of a HFD early in life has a detrimental impact on bioenergetic and mitochondrial function of tissues with metabolic and thermogenic activities, which is likely related to hippocampal metabolic changes and cognitive impairment.HighlightsHFD introduced early in life impacts mitochondrial functionDietary shift early in life leads hippocampal dysfunctionEarly life HFD exposure disrupts BAT thermogenic acitivityHFD-induced hippocampal and BAT mitochondrial dysfunction impacts cognition
Cell wall extensin arabinosylation is required for root directional response to salinity
Authors: Zou Yutao , Gigli-Bisceglia Nora , Zelm Eva van , Kokkinopoulou Pinelopi , Julkowska Magdalena M. , Besten Maarten , Nguyen Thu-Phuong , Li Hongfei , Lamers Jasper , Zeeuw Thijs de , Dongus Joram A. , Zeng Yuxiao , Cheng Yu , Koevoets Iko T. , Jørgensen Bodil , Giesbers Marcel , Vroom Jelmer , Ketelaar Tijs , Petersen Bent Larsen , Engelsdorf Timo , Sprakel Joris , Zhang Yanxia , Testerink Christa 
Published: June 2022

AbstractSoil salinity is a major contributor to crop yield losses. To improve our understanding of root responses to salinity, we developed and exploit here a real-time salt-induced tilting assay (SITA). This method follows root growth upon both gravitropic and salt challenges, revealing that root bending upon tilting is modulated by salinity, but not by osmotic stress. Next, this salt-specific response was measured in 345 natural Arabidopsis accessions and we discovered a genetic locus, encoding for the cell-wall modifying enzyme EXTENSIN ARABINOSE DEFICIENT TRANSFERASE (ExAD), to be associated with root bending in salt. Extensins are a class of structural cell wall glycoproteins [hydroxyproline-rich glycoproteins (HRGPs)] which are post-translationally modified by O-glycosylation mostly in the form of hydroxyproline (Hyp)-arabinosylation. We show that salt induces ExAD-dependent Hyp-arabinosylation, influencing root bending responses and cell wall thickness. We report that roots ofexadmutants, which lack extensin Hyp-Araf4modifications, display increased root epidermal cell wall thickness and porosity and altered gravitropic root bending in salt, as well as a reduced salt avoidance response. Our results suggest that extensin modification via Hyp-arabinosylation represents a novel salt-specific cellular process that is required for the directional response of roots exposed to salinity.
Plasma levels of Ceramides and their association with Hematocrit and Thrombocytopenia in Severe and Non-severe dengue
Authors: Jeanpierre Aashika Raagavi , Mariappan Vignesh , Green Siva Ranganathan , Mutheneni Srinivasa Rao , P Shashikala , Pillai Agieshkumar Balakrishna 
Published: June 2022

AbstractBackgroundPlasma leakage due to endothelial permeability is regarded as a hallmark process in the pathophysiology of severe dengue. In recent years, the importance of ceramide in regulating vascular tone during viral infection and metabolic diseases has gained attention. The present study aimed to evaluate the plasma levels of ceramide and its association with plasma leakage in dengue patients.MethodsThe study involved 30 dengue samples involving severe dengue (SD-10), Dengue with Warning sign (DWW-10), Dengue without Warning Sign (DWOW-10), along with other febrile illness (OFI-10) controls. Samples were collected on the day of admission (DOA), day of defervescence (DOD), and day of convalescence (DOC). Total plasma ceramides (d18:1/22:0) were quantified using RP-HPLC. The correlation between ceramides and hematocrit/platelet count was evaluated using Spearman Rho Correlation. All the statistical analyses were performed using SPSS software.ResultsDuring the febrile phase, a significant (P≤0.05) decrease in the levels of ceramides was observed in dengue compared to OFI (control). Towards the defervescences, the ceramides levels were substantially (P ≤ 0.001) elevated in dengue groups compared to baseline. Most importantly, the ceramide levels were found to be higher in SD patients compared to non-severe dengue (DWW & DWOW) and OFI, particularly at the critical phase of infection. We observed a significant negative correlation (r = -0.867, P ≤0.001) between the platelet count and ceramide levels in SD subjects. Notably, a negative correlation was observed between ceramide and hematocrit during the defervescence phase (R = -0.355, P≤0.05) in the AD group.ConclusionElevated levels of circulating plasma ceramides during the defervescence phase of severe dengue show an essential role of ceramides in disease pathogenesis, however further studies are required to ascertain it.
KPop: Accurate and scalable comparative analysis of microbial genomes by sequence embeddings
Authors: Didelot Xavier , Ribeca Paolo 
Published: June 2022

AbstractThe recent explosion in the amount of available sequencing data challenges existing analysis techniques. Here we introduce KPop, a novel versatile method based on fullk-mer spectra and dataset-specific transformations, through which thousands of assembled or unassembled microbial genomes can be quickly compared. Unlike minimizer-based methods that produce distances and have lower resolution, KPop is able to accurately map sequences onto a low-dimensional space. Extensive validation on simulated and real-life viral and bacterial datasets shows that KPop can correctly separate sequences at both species and sub-species levels even when the overall genomic diversity is low. KPop also rapidly identifies related sequences and systematically outperforms minimizer-based methods. KPop’s code is open-source and available on GitHub athttps://github.com/PaoloRibeca/KPop.
The Effects of Nonlinear Signal on Expression-Based Prediction Performance
Authors: Heil Benjamin J. , Crawford Jake , Greene Casey S. 
Published: June 2022

AbstractThose building predictive models from transcriptomic data are faced with two conflicting perspectives. The first, based on the inherent high dimensionality of biological systems, supposes that complex non-linear models such as neural networks will better match complex biological systems. The second, imagining that complex systems will still be well predicted by simple dividing lines prefers linear models that are easier to interpret. We compare multi-layer neural networks and logistic regression across multiple prediction tasks on GTEx and Recount3 datasets and find evidence in favor of both possibilities. We verified the presence of non-linear signal for transcriptomic prediction tasks by removing the predictive linear signal with Limma, and showed the removal ablated the performance of linear methods but not non-linear ones. However, we also found that the presence of non-linear signal was not necessarily sufficient for neural networks to outperform logistic regression. Our results demonstrate that while multi-layer neural networks may be useful for making predictions from gene expression data, including a linear baseline model is critical because while biological systems are highdimensional, effective dividing lines for predictive models may not be.