bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perceived biodiversity: is what we measure also what we see and hear?
Authors: Rozario Kevin , Shaw Taylor , Marselle Melissa , Oh Rachel Rui Ying , Schröger Erich , Giraldo Botero Mateo , Frey Julian , Ștefan Valentin , Müller Sandra , Scherer-Lorenzen Michael , Jaroszewicz Bogdan , Verheyen Kris , Bonn Aletta 
Published: April 2024

Abstract1. Biodiversity is crucial for human health and well-being. Perceived biodiversity - people’s subjective experience of biodiversity - seems to be particularly relevant for mental well-being.2. Using photographs and audio recordings of forests that varied in levels of species richness, we conducted two sorting studies to assess how people perceive visual and acoustic diversity and whether their perceptions align with measured tree and bird species richness (‘actual diversity’). Per study, 48 participants were asked to sort the stimuli according to any similarity-based sorting criteria they liked (‘open sorts’) and perceived diversity (‘closed sorts’).3. The main perceived visual forest characteristics identified by participants in the open visual sorts were vegetation density, light conditions, forest structural attributes and colours. The main perceived acoustic forest characteristics identified in the open acoustic sorts comprised bird song characteristics, physical properties such as volume, references to the time of day or seasonality and evoked emotions.4. Perceived visual and acoustic diversity were significantly correlated with actual tree and bird species richness, respectively. Notably, the relationship was twice as strong for the acoustic sense. The acoustic sense may thus be crucial to obtain a more thorough understanding of perceived biodiversity.5. We further computed several visual and acoustic diversity indices from the photos and audio recordings, e.g. colourfulness or acoustic complexity, and assessed their relevance for perceived and actual diversity. While all acoustic diversity indices were significantly associated with perceived acoustic diversity and bird richness, we could not identify a visual diversity index that captured perceived visual diversity and tree richness.6. Our results suggest that people can perceive species richness. Our identified visual and acoustic forest characteristics may help to better understand perceived diversity and how it differs from actual diversity. We present acoustic diversity indices that quantify aspects of perceived and actual acoustic diversity. These indices may serve as cost-efficient tools to manage and plan greenspaces to promote biodiversity and mental well-being.
Long-term Exposure to Methyl Jasmonate Increases Myrosinases TGG1 and TGG2 in Arabidopsiscoi1andmyc2,3,4Mutants
Authors: Mirzaei Mohamadreza , Poormassalehgoo Andisheh , Endo Kaichiro , Dubas Ewa , Yamada Kenji 
Published: April 2024

AbstractMyrosinase is an enzyme that activates a group of metabolites, namely glucosinolates, which are involved in the defense against herbivores and pathogens. InArabidopsis thaliana, THIOGLUCOSIDE GLUCOHYDROLASE 1 (TGG1) and TGG2 are two myrosinases that accumulate in specialized myrosin cells of rosette leaves. Here, we show that prolonged exposure to the wounding hormone methyl jasmonate (MeJA) enhancesTGG1andTGG2expression independent of the canonical jasmonic acid (JA) signaling pathway. We found that airborne MeJA treatment for up to 5-days enhanced bothTGG1andTGG2gene expression and their protein levels in Arabidopsis leaves.TGG1andTGG2gene expression did not stop in two JA signaling pathway mutants, namelycoi1-16andmyc2,3,4, after 5-days of MeJA treatment, although other typical JA responses were completely stopped in these two mutants. FAMA is a transcription factor that participates in the specification of myrosin cell development, but it does not appear to be involved inTGG1andTGG2gene expression regulation in the 5-day MeJA treatment, as its expression did not increase. Taken together, our results suggest the existence of an alternative JA signaling pathway that is activated by long-term exposure to MeJA.
Macro-environment strongly interacts with warming in a global analysis of decomposition
Authors: Schwieger Sarah , Dorrepaal Ellen , Petit Bon Matteo , Vandvik Vigdis , le Roux Elizabeth , Strack Maria , Yang Yan , Venn Susanna , van den Hoogen Johan , Valiño Fernando , Thomas Haydn J.D. , te Beest Mariska , Suzuki Satoshi , Petraglia Alessandro , Myers-Smith Isla H. , Munir Tariq Muhammad , Michelsen Anders , Løkken Jørn Olav , Li Qi , Koike Takayoshi , Klanderud Kari , Karr Ellen Haakonsen , Jónsdóttir Ingibjörg Svala , Hollister Robert D. , Hofgaard Annika , Hassan Ibrahim A. , Genxu Wang , Filippova Nina , Crowther Thomas W. , Clark Karin , Christiansen Casper T. , Casanova-Katny Angelica , Carbognani Michele , Bokhorst Stef , Björnsdóttir Katrín , Asplund Johan , Althuizen Inge , Alonso Rocío , Alatalo Juha , Agathokleous Evgenios , Aerts Rien , Sarneel Judith M. 
Published: April 2024

AbstractEmpirical studies worldwide show substantial variability in plant litter decomposition responses to warming, leaving the overall impact of climate change on this process uncertain. We conducted a meta-analysis of 109 experimental warming studies across seven continents, utilizing natural and standardized plant material, to assess the overarching effect of warming on decomposition and identify potential moderating factors.Warming influences decomposition differently across macro-environmental gradients of moisture and temperature. Negative warming effects on decomposition in warmer, low-moisture areas were counterbalanced by the positive, though not significant, warming effects in colder areas, resulting in an overall non-significant effect. We determine that at least 5.2 degrees of warming is required for a significant increase in decomposition. This is particularly relevant given the past decade’s global warmth in higher latitudes, holding a significant proportion of terrestrial carbon. Low-quality plant litter was more sensitive to warming. Therefore, future vegetation changes toward low-quality, temperature-sensitive plants could increase carbon release and reduce the net supply of stored organic matter in the soil by increasing the decomposition of low-quality litter with warming. Our findings emphasize the connection between warming responses, macro-environment, and litter characteristics, refining predictions of climate change’s consequences on key ecosystem processes and its contextual dependencies.
Lower adaptive immunity in invasive Egyptian geese compared to sympatric native waterfowls
Authors: Messina Simone , Prüter Hanna , Czirják Gábor Árpád , Costantini David 
Published: April 2024

AbstractSuccessful invasive species increase their spreading success by trading-off nutritional and metabolic resources allocated to reproduction and range expansion with other costly body functions. One proposed mechanism for the reallocation of resources is a trade-off with the immune function and the regulation of oxidative status. Relying on a panel of blood-based markers of immune function and oxidative status quantified in an invasive species (Egyptian goose) and two native competing species (mallard and mute swan) in Germany, we tested the hypothesis that the invasive species would have (i) lower investment in immune function, (ii) lower levels of oxidative damage, and (iii) no higher antioxidant defences compared to the native species. We found lower levels of adaptive immune markers (lymphocytes and immunoglobulin Y), in the invasive species compared to the two native species. Reactive oxygen metabolites, a marker of oxidative damage, were also lower in Egyptian geese compared to the other species, while levels of antioxidants were generally similar. Mute swans showed the highest levels of heterophils, lysozymes and haemolysis among the three species, possibly due to its larger body mass. Our results point to a reduced investment in adaptive immune function in the invasive species as a possible resources-saving immunological strategy due to the loss of co-evolved parasites in the new colonised habitats, as observed in a previous study. A lower investment in immune function may benefit other energy-demanding activities, such as reproduction, dispersal, and territoriality.Research highlightsOur results point to a reduced investment in adaptive immune function in invasive Egyptian geese compared to native and sympatric waterfowl species, as a possible resources-saving immunological strategy due to the loss of co-evolved parasites in the new colonised habitats.
Learning Gaussian Graphical Models from Correlated Data
Authors: Song Zeyuan , Gunn Sophia , Monti Stefano , Peloso Gina Marie , Liu Ching-Ti , Lunetta Kathryn , Sebastiani Paola 
Published: April 2024

AbstractGaussian Graphical Models (GGM) have been widely used in biomedical research to explore complex relationships between many variables. There are well established procedures to build GGMs from a sample of independent and identical distributed observations. However, many studies include clustered and longitudinal data that result in correlated observations and ignoring this correlation among observations can lead to inflated Type I error. In this paper, we propose a Bootstrap algorithm to infer GGM from correlated data. We use extensive simulations of correlated data from family-based studies to show that the Bootstrap method does not inflate the Type I error while retaining statistical power compared to alternative solutions. We apply our method to learn the GGM that represents complex relations between 47 Polygenic Risk Scores generated using genome-wide genotype data from a family-based study known as the Long Life Family Study. By comparing it to the conventional methods that ignore within-cluster correlation, we show that our method controls the Type I error well in this real example.
Escalation of intravenous fentanyl self-administration and assessment of withdrawal behavior in male and female mice
Authors: Chen Yueyi , Xiao Tiange , Kimbrough Adam 
Published: April 2024

AbstractBackgroundThe rise in overdose deaths from synthetic opioids, especially fentanyl, necessitates the development of preclinical models to study fentanyl use disorder (FUD). While there has been progress with rodent models, additional translationally relevant models are needed to examine excessive fentanyl intake and withdrawal symptoms.MethodsThe study performed intravenous self-administration (IVSA) of fentanyl in male and female C57BL/6J mice for 14 days. Mechanical pain sensitivity during withdrawal was assessed using the von Frey test. Anxiety-like behavior was evaluated via the open field test one-week into abstinence and incubation of craving for fentanyl was assessed four weeks into abstinence.ResultsBoth male and female mice demonstrated a significant escalation in fentanyl intake over the 14 days of self-administration, with significant front-loading observed in the final days of self-administration. Increased mechanical pain sensitivity was present from 36- to 48-hour into withdrawal and increased anxiety-like behavior was found 1 week into abstinence. Four weeks into abstinence, mice showed significantly higher active lever pressing than the final self-administration session prior to abstinence.ConclusionsThe study establishes a translationally relevant mouse model of IVSA of fentanyl, effectively encapsulating critical aspects of FUD, including escalation of drug intake, front-loading behavior, withdrawal symptoms, and prolonged craving for drug into abstinence. This model offers a robust basis for further exploration into behavioral and neurobiological mechanisms involved in fentanyl dependence and potential therapeutic strategies.
RUNX1 is Expressed in a Subpopulation of Dermal Fibroblasts and Higher RUNX1 Levels are Associated with the Severity of Systemic Sclerosis
Authors: Parvizi Rezvan , Gong Zhiyun , Jarnagin Helen C. , Toledo Diana M. , Abel Tamar R. , Popovich Dillon , Morrisson Madeline J. , Shenk Sasha , Hinchcliff Monique E. , Garlick Jonathan A. , Pioli Patricia A. , Whitfield Michael L. 
Published: April 2024

AbstractThe activation of Runt-related transcription factor 1 (RUNX1) in fibroblasts has been implicated in wound healing and fibrosis; however, the role of RUNX1 in the fibrotic progression of the autoimmune disease systemic sclerosis (SSc) is not known. Through gene expression analysis, we have demonstrated an association between the severity of dermal fibrosis and the expression levels ofRUNX1in the skin of patients with SSc. Additionally, we identified hypomethylated CpG sites proximal to theRUNX1gene, implicating their potential role in the increased expression ofRUNX1. Analysis of single-cell RNA-seq data from skin biopsies of individuals with SSc revealed thatRUNX1is higher in subpopulations of fibroblasts enriched in SSc, which are believed to contribute to fibrosis. Lastly, modulation ofRUNX1activity using an inhibitor caused a reduction in fibroblast contraction and proliferation rates. Altogether, this study is the first to demonstrate a potential role forRUNX1in the pathogenesis of systemic sclerosis dermal fibrosis.
BioEncoder: a metric learning toolkit for comparative organismal biology
Authors: Lürig Moritz D. , Di Martino Emanuela , Porto Arthur 
Published: April 2024

AbstractIn the realm of biological image analysis, deep learning (DL) has been a transformative force. Tasks like finding areas of interest within an image (segmentation) and/or sorting images into groups (classification), can now be automated and achieve unprecedented efficiency and accuracy. However, conventional DL methods are challenged by large-scale biodiversity datasets, which are characterized by unbalanced classes and small phenotypic differences between them. Here we present BioEncoder, a user-friendly toolkit for metric learning, which overcomes the aforementioned challenges by focussing on learning relationships between individual data points rather than on the separability of classes. This approach simplifies training of robust image classification models for biologists, democratizing access to advanced DL techniques. BioEncoder is encapsulated in a Python package, crafted for ease of use and flexibility across diverse datasets. It features taxon-agnostic data loaders, custom augmentation options, and streamlined hyperparameter adjustments through text-based configuration files. The toolkit’s significance lies in its potential to unlock new possibilities in biological image analysis - from phenomics and disease diagnosis to species identification and ecosystem monitoring. BioEncoder focuses on the urgent need for toolkits bridging the gap between complex DL methodologies and practical applications in biological research.
A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores
Authors: Fatapour Yasaman , Brody James P. 
Published: April 2024

AbstractGenotype to phenotype prediction is a central problem in biology and medicine. Machine learning is a natural tool to address this problem. However, a person’s genotype is usually represented by a few million single-nucleotide polymorphisms and most datasets only have a few thousand patients. Thus, this problem typically has many more predictors than the number of samples (patients), making it unsuitable for machine learning.The objective of this paper is to examine the efficacy of a compact genotype representation, which employs a limited number of predictors, in predicting a person’s phenotype through the application of machine learning.We characterized a person’s genotype using chromosome-scale length variation, a measure that is computed as the average value of reported log R ratios across a portion of a chromosome. We computed these numbers from data collected by the NIH All of Us program. We used the AutoML function (h2o.ai) in binary classification mode to identify the best models to differentiate between male/female, Black/white, white/Asian, and Black/Asian. We also used the AutoML function in regression mode to predict the height of people based on their age and genotype.Our results showed that we could effectively classify a person, using only information from chromosomes 1-22, as Male/Female (AUC=0.9988±0.0001), White/Black (AUC=0.970± 0.002), Asian/White (AUC=0.877± 0.002), and Black/Asian (AUC=0.966± 0.002). This approach also effectively predicted height.In conclusion, we have shown that this compact representation of a person’s genotype, along with machine learning, can effectively predict a person’s phenotype.
Osmosensing in trabecular meshwork cells
Authors: Baumann Jackson M. , Yarishkin Oleg , Lakk Monika , Rudzitis Christopher N. , Tseng Yun Ting , Križaj David 
Published: April 2024

ABSTRACTAqueous humor drainage from the anterior eye constitutes a key determinant of intraocular pressure (IOP) under homeostatic and pathological conditions. Swelling of the trabecular meshwork (TM) increases its flow resistance but the mechanisms that sense and transduce osmotic gradients remain poorly understood. We used optical molecular analyses, optical imaging and electrophysiology to investigate TM osmotransduction and its role in calcium and chloride homeostasis. Anisosmotic conditions elicited proportional changes in TM cell volume. Swelling, but not shrinking, evoked increases in intracellular calcium concentration [Ca2+]TM. Hypotonicity-evoked calcium signals were sensitive to HC067047, a selective blocker of TRPV4 channels, whereas the agonist GSK1016790A promoted swelling under isotonic conditions. TRPV4 inhibition partially suppressed hypotonicity-induced volume increases and reduced the magnitude of the swelling-induced membrane current, with a substantial fraction of the swelling-evoked current abrogated by Cl-channel antagonists DIDS and niflumic acid. The volume-sensing transcriptome of primary human TM cells showed expression of TRPV4, TRPM4, AQP1, and TMEMC3B genes. Cl-channel expression was dominated by ANO6 transcripts, auxiliary levels of ANO3, ANO7 and ANO10 and modest expression of LTTRC genes that encode volume-activated anion channels. Thus, TRPV4-mediated cation influx works with Cl-efflux to sense and respond to osmotic stress, potentially contributing to pathological swelling, calcium overload and intracellular signaling that could exacerbate functional disturbances in inflammatory disease and glaucoma.
Ketamine can produce oscillatory dynamics by engaging mechanisms dependent on the kinetics of NMDA receptors
Authors: Adam Elie , Kowalski Marek , Akeju Oluwaseun , Miller Earl K. , Brown Emery N. , McCarthy Michelle M. , Kopell Nancy 
Published: April 2024

AbstractKetamine is an NMDA-receptor antagonist that produces sedation, analgesia and dissociation at low doses and profound unconsciousness with antinociception at high doses. At high and low doses, ketamine can generate gamma oscillations (>25 Hz) in the electroencephalogram (EEG). The gamma oscillations are interrupted by slow-delta oscillations (0.1-4 Hz) at high doses. Ketamine’s primary molecular targets and its oscillatory dynamics have been characterized. However, how the actions of ketamine at the subcellular level give rise to the oscillatory dynamics observed at the network level remains unknown. By developing a biophysical model of cortical circuits, we demonstrate how NMDA-receptor antagonism by ketamine can produce the oscillatory dynamics observed in human EEG recordings and non-human primate local field potential recordings. We have discovered how impaired NMDA-receptor kinetics can cause disinhibition in neuronal circuits and how a disinhibited interaction between NMDA-receptor-mediated excitation and GABA-receptor-mediated inhibition can produce gamma oscillations at high and low doses, and slow-delta oscillations at high doses. Our work uncovers general mechanisms for generating oscillatory brain dynamics that differs from ones previously reported, and provides important insights into ketamine’s mechanisms of action as an anesthetic and as a therapy for treatment-resistant depression.
qMAP enabled microanatomical mapping of human skin aging
Authors: Han Kyu Sang , Sander Inbal B. , Kumer Jacqueline , Resnick Eric , Booth Clare , Cheng Guoqing , Im Yebin , Starich Bartholomew , Kiemen Ashley L. , Phillip Jude M. , Reddy Sashank , Joshu Corrine E. , Sunshine Joel C. , Walston Jeremy D. , Wirtz Denis , Wu Pei-Hsun 
Published: April 2024

AbstractAging is a major driver of diseases in humans. Identifying features associated with aging is essential for designing robust intervention strategies and discovering novel biomarkers of aging. Extensive studies at both the molecular and organ/whole-body physiological scales have helped determined features associated with aging. However, the lack of meso-scale studies, particularly at the tissue level, limits the ability to translate findings made at molecular scale to impaired tissue functions associated with aging. In this work, we established a tissue image analysis workflow - quantitative micro-anatomical phenotyping (qMAP) - that leverages deep learning and machine vision to fully label tissue and cellular compartments in tissue sections. The fully mapped tissue images address the challenges of finding an interpretable feature set to quantitatively profile age-related microanatomic changes. We optimized qMAP for skin tissues and applied it to a cohort of 99 donors aged 14 to 92. We extracted 914 microanatomic features and found that a broad spectrum of these features, represented by 10 cores processes, are strongly associated with aging. Our analysis shows that microanatomical features of the skin can predict aging with a mean absolute error (MAE) of 7.7 years, comparable to state-of-the-art epigenetic clocks. Our study demonstrates that tissue-level architectural changes are strongly associated with aging and represent a novel category of aging biomarkers that complement molecular markers. Our results highlight the complex and underexplored multi-scale relationship between molecular and tissue microanatomic scales.
Generation of hiPSC-derived brain microvascular endothelial cells using a combination of directed differentiation and transcriptional reprogramming strategies
Authors: Cui Aomeng , Patel Ronak , Bosco Patrick , Akcan Ugur , Richters Emily , Delgado Paula Barrilero , Agalliu Dritan , Sproul Andrew A. 
Published: April 2024

SUMMARYThe blood-brain barrier (BBB), formed by specialized brain microvascular endothelial cells (BMECs), regulates brain function in health and disease.In vitromodeling of the human BBB is limited by the lack of robust hiPSC protocols to generate BMECs. Here, we report generation, transcriptomic and functional characterization of reprogrammed BMECs (rBMECs) by combining hiPSC differentiation into BBB-primed endothelial cells and reprogramming with two BBB transcription factors FOXF2 and ZIC3. rBMECs express a subset of the BBB gene repertoire including tight junctions and transporters, exhibit stronger paracellular barrier properties, lower caveolar-mediated transcytosis, and similar p-Glycoprotein activity compared to primary HBMECs. They can acquire an inflammatory phenotype when treated with oligomeric Aβ42. rBMECs integrate with hiPSC-derived pericytes and astrocytes to form a 3D neurovascular system using the MIMETAS microfluidics platform. This novel 3D system resembles thein vivoBBB at structural and functional levels to enable investigation of pathogenic mechanisms of neurological diseases.