bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Biomarkers of recovery: characterizing trophic flow following ecological restoration”
Authors: Spindel Nathan B. , Galloway Aaron W. E. , Schram Julie B. , Mcneill Gwiisihlgaa Daniel , Bellis Sgiids Kung Vanessa , Guujaaw Niisii , Yakgujanaas Jaasaljuus , Thompson Markus , Lee Lynn C. , Okamoto Daniel K. 
Published: November 2024

AbstractCoastal kelp forests are important sources of primary productivity and provide essential habitat and ecosystem services. In many areas around the world, the formation and persistence of urchin barrens threatens kelp forest ecosystems. Over the past several decades, restoration efforts have emerged aiming to increase the abundance of foundation species like kelp in such systems. However, we lack a comprehensive understanding of how successful kelp restoration affects the nutritional landscape and the fitness of kelp forest herbivores. We bridge this knowledge gap with a Before-After-Control-Impact Paired Series (BACIPS) focused on kelp forest restoration where reductions of herbivorous sea urchins in Haida Gwaii resulted in substantial increases in kelp abundance in habitat previously characterized as barrens. Specifically, we document body size specific shifts in the fatty acid (FA) profiles of red sea urchins (Mesocentrotus franciscanus) and northern abalone (Haliotis kamtschatkana). FAs associated with bacteria and diatoms were elevated in tissues of urchins and abalone in barrens habitat while kelp biomarkers were elevated in restored kelp forest habitat. For urchins, these shifts tracked the increase in gonad mass following kelp forest recovery. For abalone, these results varied depending on animal body size. Specifically, abalone exhibited a continuous size-specific shift from biofilm-associated markers at small sizes to kelp-associated markers as animals increased in size. For both species, a marked increase in essential fatty acids was observed following kelp restoration. Our results demonstrate kelp restoration via sea urchin reduction enhances not only the quantity but also the quality and diversity of food in previously degraded habitats, and subsequently enhances the amount and nutritional quality of roe (i.e., gonads) in sea urchins therein.
GOBoost: Leveraging Long-Tail Gene Ontology Terms for Accurate Protein Function Prediction
Authors: Zhang Lei , Wang Yang , Chen Xiao , Hou Jie , Si Dong , Ding Rui , Jiang Bo , Ledenko Hailey , Cao Renzhi 
Published: November 2024

AbstractMotivationWith the advancement of deep learning, researchers have increasingly proposed computational methods based on deep learning techniques to predict protein function. However, many of these methods treat protein function prediction as a multi-label classification problem, often overlooking the long-tail distribution of functional labels (i.e., Gene Ontology Terms) in datasets. To address this issue, we propose the GOBoost method, which incorporates the proposed long-tail optimization ensemble strategy. Besides, GOBoost introduces the proposed global-local label graph module and multi-granularity focal loss function to enhance long-tail functional information, mitigate the long-tail phenomenon, and improve overall prediction accuracy.ResultsWe evaluate GOBoost and other state-of-the-art (SOTA) protein function prediction methods on the PDB and AF2 datasets. The GOBoost outperformed SOTA methods across all evaluation metrics on both datasets. Notably, in the AUPR evaluation on the PDB test set, GOBoost improved by 10.71%, 35.91%, and 22.71% compared to the SOTA HEAL method in the MF, BP, and CC functions. The experimental results demonstrate the necessity and superiority of designing models from the label long-tail distribution perspective.Availabilityhttps://github.com/Cao-Labs/GOBoostContactcaora@plu.edu
Isolated Mouse Adult Cardiomyocytes Display Minimal Mitochondrial ATP Demand and Maximal Reliance on Glycolysis
Authors: Mattam Ushodaya , Talari Noble Kumar , Sathyanarayana Ashish Rao , Mia Sobuj , Frazier James , Slone Sam , Drosatos Konstantinos , Chella Krishnan Karthickeyan 
Published: November 2024

ABSTRACTMitochondrial maladaptation is a hallmark of heart failure, contributing to impaired energy production and contractile dysfunction. Understanding the bioenergetics of cardiomyocytes under healthy and pathological conditions is critical for characterizing mitochondrial maladaptation. While adult cardiomyocytes from rodents are a widely used model, recent studies have reported oligomycin insensitivity in these cells, a phenomenon often overlooked. This has led to incomplete assessments of key bioenergetic parameters, such as ATP-linked respiration and glycolytic capacity, focusing primarily on basal and maximal respiration. In this study, we performed a comprehensive characterization of bioenergetic and glycolytic profiles in three cardiomyocyte models: neonatal rat ventricular myocytes (NRVMs), human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), and mouse adult cardiomyocytes (mouse ACMs). Our findings demonstrate distinct metabolic adaptations in mouse ACMs, revealing critical insights into mitochondrial function, ATP demand, and glycolytic reliance. These results underscore the importance of selecting appropriate cellular models for studying mitochondrial bioenergetics in cardiac physiology and pathology.
Replication of DNA containing trinucleotide repeats by the bacteriophage T7 replisome
Authors: Lee Seung-Joo , Mitsunobu Hitoshi , Hernandez Alfredo J. 
Published: November 2024

AbstractTrinucleotide repeats in the human genome are implicated in various neurodegenerative diseases. The tendency of these repetitive DNA sequences to form non-B DNA structures can cause abnormal replication, leading to genomic instability. This instability contributes to disease progression, though the underlying mechanisms are not fully understood. We investigated the replication of DNA containing CAG and CTG trinucleotide repeats using individual components of the T7 bacteriophage replication machinery, as well as the complete replisome. Our results show that repeats in linear single-stranded DNA (ssDNA) inhibit the activity of T7 DNA polymerase and ssDNA-binding proteins, with a more pronounced effect observed in CTG repeats compared to CAG repeats. Minicircle templates containing CTG repeats exhibited robust DNA synthesis on both the leading and lagging strands, though synthesis was not enhanced by the T7 gene 2.5 ssDNA-binding protein. The lagging strand products generated from the CTG repeat minicircle were significantly longer than those from random sequence templates, and their lengths were not extended by the presence of T7 gene 2.5 protein. When the repeated sequences were incorporated into the T7 phage genome, heterogeneity was observed downstream of the repeats, depending on their length. We propose that aberrant extension occurs predominantly in the lagging strand, driven by dynamic interactions between the repeated sequences and the DNA replisome. This study may provide a foundation for understanding the mechanisms underlying the extension or deletion of repetitive genomic regions.
Enzyme-constrained Metabolic Model ofTreponema pallidumIdentified Glycerol-3-phosphate Dehydrogenase as an Alternate Electron Sink
Authors: Shahreen Nabia , Chowdhury Niaz Bahar , Stone Edward , Knobbe Elle , Saha Rajib 
Published: November 2024

ABSTRACTTreponema pallidum, the causative agent of syphilis, poses a significant global health threat. Its strict intracellular lifestyle and challenges inin vitrocultivation have impeded detailed metabolic characterization. In this study, we present iTP251, the first genome-scale metabolic model ofT. pallidum, reconstructed and extensively curated to capture its unique metabolic features. These refinements included the curation of key reactions such as pyrophosphate-dependent phosphorylation and pathways for nucleotide synthesis, amino acid synthesis, and cofactor metabolism. The model demonstrated high predictive accuracy, validated by a MEMOTE score of 92%. To further enhance its predictive capabilities, we developed ec-iTP251, an enzyme-constrained version of iTP251, incorporating enzyme turnover rate and molecular weight information for all reactions having gene-protein-reaction associations. Ec-iTP251 provides detailed insights into protein allocation across carbon sources, showing strong agreement with proteomics data (Pearson’s correlation of 0.88) in the central carbon pathway. Moreover, the thermodynamic analysis revealed that lactate uptake serves as an additional ATP-generating strategy to utilize unused proteomes, albeit at the cost of reducing the driving force of the central carbon pathway by 27%. Subsequent analysis identified glycerol-3-phosphate dehydrogenase as an alternative electron sink, compensating for the absence of a conventional electron transport chain while maintaining cellular redox balance. These findings highlightT. pallidum’s metabolic adaptations for survival and redox balance in intracellular environments, providing a foundation for future research into its unique bioenergetics.IMPORTANCEThis study advances our understanding ofTreponema pallidum, the syphilis-causing pathogen, through the reconstruction of iTP251, the first genome-scale metabolic model for this organism, and its enzyme-constrained version, ec-iTP251. The work addresses challenges of studyingT. pallidumdue to its strict intracellular nature and difficulties inin vitrocultivation. Validated with strong agreement to proteomics data, the model demonstrates high predictive reliability. Key insights include unique metabolic adaptations such as lactate uptake for ATP production and alternative redox-balancing mechanisms. These findings provide a robust framework for future studies aimed at unraveling the pathogen’s survival strategies and identifying potential metabolic vulnerabilities.
A Review on Calibration Methods of Cancer Simulation Models
Authors: Zhang Yichi , Alagoz Oguzhan 
Published: November 2024

AbstractCalibration, a critical step in the development of simulation models, involves adjusting unobservable parameters to ensure that the outcomes of the model closely align with observed target data. This process is particularly vital in cancer simulation models with a natural history component where direct data to inform natural history parameters are rarely available. This work reviews the literature of cancer simulation models with a natural history component and identifies the calibration approaches used in these models with respect to the following attributes: calibration target, goodness-of-fit (GOF) measure, parameter search algorithm, acceptance criteria, and stopping rules. After a comprehensive search of the PubMed database from 1981 to June 2023, 68 studies were included in the review. Nearly all (n=66) articles specified the calibration targets, and most articles (n=56) specified the parameter search algorithms they used, whereas goodness-of-fit metric (n=51) and acceptance criteria/stopping rule (n=45) were reported for fewer times. The most frequently used calibration targets were incidence, mortality, and prevalence, whose data sources primarily come from cancer registries and observational studies. The most used goodness-of-fit measure was weighted mean squared error. Random search has been the predominant method for parameter search, followed by grid search and Nelder-mead method. Machine learning-based algorithms, despite their fast advancement in the recent decade, has been underutilized in the cancer simulation models. More research is needed to compare different parameter search algorithms used for calibration.Key pointsThis work reviewed the literature of cancer simulation models with a natural history component and identified the calibration approaches used in these models with respect to the following attributes: calibration target, goodness-of-fit (GOF) measure, parameter search algorithm, acceptance criteria, and stopping rules.Random search has been the predominant method for parameter search, followed by grid search and Nelder-mead method.Machine learning-based algorithms, despite their fast advancement in the recent decade, has been underutilized in the cancer simulation models. Furthermore, more research is needed to compare different parameter search algorithms used for calibration.
Identifying resilience factors for adolescent mental health with cyberbullying victimisation as a risk factor
Authors: Kandola Aaron , Mansfield Rosie , Kelly Yvonne , Rahman Yasmin , Choi Karmel , Hollis Chris , Townsend Ellen , Patalay Praveetha 
Published: November 2024

AbstractPromoting resilience can reduce the mental health risks of cyberbullying victimisation in adolescents.We conducted a longitudinal cohort study with 9,969 adolescents (Millennium Cohort Study (MCS)) at ages 14-15 (baseline) and 17 (follow-up). We replicated our analyses in 4,240 adolescents (Longitudinal Study of Australian Children). The outcome was psychological distress at follow-up. Cyberbullying victimisation was a single-item question. Aim one identified modifiable resilience factors (exposures) associated with psychological distress. Aim two examined whether these resilience factors (moderators) interacted with the cyberbullying-distress association.478/1,466 baseline variables were associated with distress after confounder adjustment (aim one). 31/478 potential resilience factors moderated the cyberbullying-distress association. 15 models replicated in the individual (n=8, e.g., happiness with friends), family and friends (n=3, e.g., sexual activities), structural (n=2, e.g., income sources), and learning environment (n=2, e.g., misbehaviour) domains.We identified several factors for further research on developing interventions to reduce adolescent cyberbullying mental health risks.
Respiratory acclimatization and psychomotor performance after rapid ascent and during 3 weeks at 3100 m. A prospective cohort study in healthy
Authors: Muralt Lara , Lichtblau Mona , Aeschbacher Sayaka S , Bisang Maya , von Gruenigen Kay , Sooronbaev Talant M. , Ulrich Silvia , Bloch Konrad E , Furian Michael 
Published: November 2024

ABSTRACTBackgroundThe acclimatization to high altitudes over several weeks is not extensively studied. Repeated physiological assessments were performed in healthy lowlanders staying at 3100m for 3 weeks. We hypothesized that over the course of 3 weeks, the arterial oxygen saturation (SpO2) improves and has favorable effects on psychomotor vigilance, postural control, and sleep.Methods16 healthy volunteers (23-33y) underwent sleep studies during 1 night in Bishkek (760m), and during nights 1, 8 and 22 at Too-Ashu (3100m), Kyrgyzstan. The day after, reaction time (psychomotor vigilance test reaction time test, PVT) and postural control (center of gravity path length on balance board [COPL]) were assessed.ResultsCompared to 760m, mean nocturnal SpO2dropped in the first night at 3100m from mean±SD 94.8±1.9% to 86.3±2.9% and recovered partially to 89.8±1.5% after 3 weeks (P<0.05 both comparisons to 760m). Corresponding median (quartiles) oxygen desaturation indices were 1.0/h(0.3;2.2), 6.5/h(4.5;12.1) and 6.4/h(4.2;11.1) time in bed (P<0.05 both comparisons to 760m). Median (quartiles) reaction times were 226ms(212;231), 236ms(210;259) and 228ms(212;246), P=NS, all comparisons. COPL worsened from 25.1±4.1cm to 27.1±4.1cm (P<0.05) and 26.4±3.7cm (P=NS compared to 760m).ConclusionIn healthy lowlanders staying at 3100m, nocturnal SpO2increased over 3 weeks after an initial drop but did not reach 760m baseline values. Postural control was impaired in the first week of acute exposure to high altitude despite improvements in hypoxemia. Altitude exposure had no effect on reaction time. Thus, acute and prolonged exposure to hypobaric hypoxia has differential effects on oxygenation, control of breathing, postural control and reaction time.
The role of natural language processing in cancer care: a systematic scoping review with narrative synthesis
Authors: Sun Mengxuan , Reiter Ehud , Duncan Lisa , Adam Rosalind 
Published: November 2024

AbstractObjectivesTo review studies of Natural Language Processing (NLP) systems that assist in cancer care, explore use cases and summarize current research progress.MethodsA systematic scoping review, searching six databases (1) MEDLINE, (2) Embase, (3) IEEE Xplore, (4) ACM Digital Library, (5) Web of Science, and (6) ACL Anthology. Studies were included that reported NLP systems that had been used to improve cancer management by patients or clinicians. Studies were synthesized descriptively and using content analysis.ResultsTwenty-nine studies were included. Studies mainly applied NLP in mixed cancer types (n=10, 34.48%) and breast cancer (n=8, 27.59%). NLP was used in four main ways: (1) to support patient education and self-management; (2) to improve efficiency in clinical care by summarizing, extracting, and categorizing data, and supporting record-keeping; (3) to support prevention and early detection of patient problems or cancer recurrence; and (4) to improve cancer treatment by supporting clinicians to make evidence-based treatment decisions. Studies highlighted a wide variety of use cases for NLP technologies in cancer care. However, few technologies had been evaluated within clinical settings, none were evaluated against clinical outcomes, and none had been implemented into clinical care.ConclusionNLP has the potential to improve cancer care via several mechanisms, including information extraction and classification, which could enable automation and personalization of care processes. Additionally, NLP tools such as chatbots show promise in improving patient communication and support. However, there are deficiencies in the evaluation and clinical integration challenges. Interdisciplinary collaboration between computer scientists and clinicians will be essential if NLP technologies are to fulfil their potential to improve patient experience and outcomes. Registered Protocol:https://doi.org/10.17605/OSF.IO/G9DSR
In utero exposure to per – and polyfluoroalkyl substances (PFAS) associates with altered human infant T helper cell development
Authors: Meléndez Darline Castro , Laniewski Nathan , Jusko Todd A. , Qiu Xing , Paige Lawrence B. , Rivera-Núñez Zorimar , Brunner Jessica , Best Meghan , Macomber Allison , Leger Alena , Kannan Kurunthachalam , Miller Richard Kermit , Barrett Emily S. , O’Connor Thomas G. , Scheible Kristin 
Published: November 2024

AbstractBackgroundEnvironmental exposures to chemical toxicants during gestation and infancy can dysregulate multiple developmental processes, causing lifelong effects. There is compelling evidence of PFAS-associated immunotoxicity in adults and children. However, the effect of developmental PFAS exposure on infant T-cell immunity is unreported, and, if present, could be implicated in immune-related health outcomes.ObjectivesWe seek to model longitudinal changes in CD4+ T-cell subpopulations from birth through 12 months and their association with in-utero PFAS exposure and postnatal CD4+ T-cell frequencies and functions.MethodsMaternal-infant dyads were recruited as part of the UPSIDE-ECHO cohort during the first trimester between 2015 and 2019 in Rochester, New York; dyads were followed through the infant’s first birthday. Maternal PFAS concentrations (PFOS, PFOA, PFNA, and PFHXS) were quantified in serum during the second trimester using high-performance liquid chromatography and tandem mass spectrometry. Infant lymphocyte frequencies were assessed at birth, 6- and 12-months using mass cytometry and high-dimensional clustering methods. Linear mixed-effects models were employed to analyze the relationship between maternal PFAS concentrations and CD4+ T-cell subpopulations (n=200). All models included a PFAS and age interaction and were adjusted for parity, infant sex, and pre-pregnancy body mass index.ResultsIn-utero PFAS exposure correlated with multiple CD4+ T-cell subpopulations in infants. The greatest effect sizes were seen in T-follicular helper (Tfh) and T-helper 2 (Th2) cells at 12 months. A log2-unit increase in PFOS was associated with lower Tfh [0.17% (95%CI: −0.30, −0.40)] and greater Th2 [0.27% (95%CI: 0.18, 0.35)] cell percentages at 12 months. Similar trends were observed for PFOA, PFNA, and PFHXS.DiscussionMaternal PFAS exposures correlate with cell-specific changes in the infant T-cell compartment, including key CD4+ T-cell subpopulations that play central roles in coordinating well-regulated, protective immunity. Future studies into the role of PFAS-associated T-cell distribution and risk of adverse immune-related health outcomes in children are warranted.
Sex and hormonal effects on drug cue-reactivity and its regulation in human addiction
Authors: Huang Yuefeng , Butelman Eduardo R. , Ceceli Ahmet O. , Kronberg Greg , King Sarah G. , McClain Natalie E. , Wong Yui Ying , Boros Maggie , Drury K Rachel , Sinha Rajita , Alia-Klein Nelly , Goldstein Rita Z. 
Published: November 2024

AbstractObjectiveTo study the sex and hormonal effects on cortico-striatal engagement during drug cue-reactivity and its regulation focusing on drug reappraisal.MethodsForty-nine men (age=41.96±9.71) with heroin use disorder (HUD) and 32 age-matched women (age=38.85±9.84) with HUD (n=16) or cocaine use disorder (CUD; n=16) were scanned using functional MRI, with a subgroup of women scanned twice, during the late-follicular and mid-luteal phases, to examine sex and menstrual phase differences in cortico-striatal drug cue-reactivity and its cognitive reappraisal and their correlations with ovarian hormones and drug craving.ResultsWomen showed higher medial prefrontal cortex (PFC) drug cue-reactivity while men showed higher frontal eye field (FEF)/dorsolateral PFC (dlPFC) drug reappraisal as associated with lower cue-induced drug craving. In the women, drug cue-reactivity was higher during the follicular phase in the FEF/dlPFC, whereas drug reappraisal was higher during the luteal phase in the anterior PFC/orbitofrontal cortex. The more the estradiol during the follicular vs. luteal phase (Δ), the higher the Δdrug cue-reactivity in the vmPFC, which also correlated with higher Δdrug craving (observed also in the inferior frontal gyrus). The more this Δestradiol, the lower the Δdrug reappraisal in the vmPFC, anterior PFC and striatum. Conversely, Δprogesterone/estradiol ratio was positively associated with Δdrug reappraisal in the dlPFC.ConclusionsCompared to men, women with addiction show more cortico-striatal reactivity to drug cue exposure and less PFC activity during drug reappraisal, driven by the follicular compared to luteal phase and directly related to craving and fluctuations in estrogen and progesterone with the former constituting a vulnerability and the latter a protective factor. This study provides insights for developing precisely timed and hormonally informed treatments for women with addiction.