bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gamma-hydroxybutyrate to promote slow-wave sleep in major depressive disorder: a randomized crossover trial
Authors: Bavato Francesco , Schnider Laura K. , Dornbierer Dario A. , Di Floriano Julia R. , Friedli Nicole , Janki Marina , Quednow Boris B. , Landolt Hans-Peter , Bosch Oliver G. , Seifritz Erich 
Published: October 2024

AbstractIn major depressive disorder (MDD), main clinical features include insomnia and increased daytime sleepiness. However, specific treatment options to promote sleep in MDD are limited. Gamma-hydroxybutyrate (GHB, clinically administered as sodium oxybate) is a GHB/GABABreceptor agonist used clinically in narcolepsy, where it promotes restorative slow-wave sleep (SWS) while reducing next-day sleepiness. Therefore, we performed a randomized, placebo- and active comparator-controlled, double-blind, crossover trial to investigate the sleep-promoting properties of GHB in individuals with MDD. Outpatients aged 20-65 years fulfilling the DSM-V criteria for MDD were enrolled. A single dose of GHB (50mg/kg) was compared with a single dose of the clinical competitor trazodone (1.5 mg/kg) and placebo. Of 29 randomized patients, 23 received at least one intervention and were included in the analysis. Primary outcomes were slow wave sleep ([SWS], as % of total sleep time [TST]) assessed by polysomnography and next-day vigilance (median response time and number of lapses in the psychomotor vigilance test [PVT]). GHB robustly prolonged SWS compared to both trazodone and placebo. GHB also prolonged TST and enhanced sleep efficiency (TST % of time-in-bed), while reducing sleep stages N1, N2, and wake-after-sleep-onset. While the median response time on the PVT was unaffected, GHB reduced the number of lapses compared to trazodone and placebo. No serious adverse events occurred. A single nocturnal dose of GHB effectively promotes SWS and shows more favorable effects on next-day vigilance than trazodone and placebo. Future studies should investigate GHB in clinical settings, including repeated administration.
Increasing Representativeness in theAll of UsCohort Using Inverse Probability Weighting
Authors: Kambara Manoj S. , Sharma Shivam , Spouge John L. , Jordan I. King , Mariño-Ramírez Leonardo 
Published: October 2024

AbstractLarge-scale population biobanks rely on volunteer participants, which may introduce biases that compromise the external validity of epidemiological studies. We characterized the volunteer participant bias for theAll of UsResearch Program cohort and developed a set of inverse probability (IP) weights that can be used to mitigate this bias. TheAll of Uscohort is older, more female, more educated, more likely to be covered by health insurance, less White, less likely to drink or smoke, and less healthy compared to the US population. IP weights developed via comparison of a nationally representative database eliminated the observed biases for all demographic and lifestyle characteristics and reduced the observed disease prevalence differences. IP weights also impact genetic associations with type 2 diabetes across diverse ancestry cohorts. We provide our IP weights as a community resource to increase the representativeness and external validity of theAll of Uscohort.
The Multidimensional Assessment of Parenting Scale: Youth Report Form in a Clinical Sample
Authors: Hogan Christina M , Beckmann Emily , Maron Micaela , Sutton Kelsey , Highlander April , Pielech Melissa , Wolff Jennifer C , Davis Thamara , Parent Justin 
Published: October 2024

AbstractObjectiveThe Multidimensional Assessment of Parenting Scale (MAPS) was developed to assess a wide range of behaviors across positive and negative domains of parenting. This study aims to expand the utility of the MAPS by evaluating a youth-report version which provides an additional perspective on parenting practices.MethodThe study evaluated the youth-report form of the MAPS (MAPS-Y) in a large clinical population (N= 628) ranging from middle childhood (8-12) to adolescence (13-17) who were admitted to partial and inpatient psychiatric units. Youth and their caregivers completed the parent and youth versions of the MAPS questionnaire, and measures of child and adolescent psychopathology, emotion regulation, family context, and adversity. Analyses of factor structure, reliability, agreement, and validity were performed. The study also examined a short form of the MAPS-Y for reliability and validity.ResultsCFA and model fit indices indicated that all items loaded as expected onto subscales and with good fit. Analyses support strong reliability. The factor structure of the youth-report was invariant across developmental stages, included both positive and negative domains, and demonstrated strong psychometric properties. The MAPS-Y short form demonstrated strong validity and reliability.ConclusionThe youth-report of the MAPS and its short form are appropriate for use among children and adolescents experiencing acute clinical symptoms. The MAPS youth-report will allow for nuanced, in-depth assessment of the parenting behaviors beyond parent-report that are critical to treatment outcomes in youth.
Early Prenatal Nitrate Exposure and Birth Outcomes: A Study of Iowa’s Public Drinking Water (1970-1988)
Authors: Semprini Jason 
Published: October 2024

AbstractBackgroundDespite the biological mechanisms linking prenatal nitrate exposure to birth outcomes, epidemiological research has been inconclusive. The evidence-base has been limited by where and how nitrate exposure was measured, and the spurious correlation between geotemporal nitrate heterogeneity and unmeasurable factors contributing to gestational age and birth weight.ObjectiveWe linked Iowa water quality data and birth records to estimate the independent association between early prenatal nitrate exposure and birth outcomes.MethodsAccessing Community Water Supply Quality Data, we calculated the median nitrate (mg/L) level for each county-date. With birth certificate microdata from the National Center for Health Statistics, we linked every Iowa birth (1970-1988) to a county-level nitrate measure within thirty days of conception. The outcomes were gestational age (weeks), preterm birth (< 37 weeks), birth weight (g), and low birth weight (< 2500 g). Nitrate exposure was first measured as a “dose-response” continuous variable, then as four binary variables (>10 mg/L, >5 mg/L, > 0.1 mg/L, > 0.0 mg/L). We constructed linear regression models which controlled for maternal and paternal characteristics, and county-year and year-month fixed-effects to account for unobservable annual variation between counties and longitudinal variation within all counties.ResultsAmong 357,741 births, mean nitrate exposure was 4.2 mg/L. Early prenatal exposure to >0.1 mg/L nitrate was associated preterm birth (Est. = +0.66%-points; C.I. = 0.31, 1.01). Early prenatal exposure to 5 mg/L nitrate was associated with low birth weight (Est. = +0.33%-points; C.I. = 0.03, 0.63). The associations between elevated exposure to nitrate and any birth outcomes did not differ from lower levels of exposure.DiscussionPrenatal exposure to nitrate below the >10 mg/L standard may cause harm. Since establishing this standard in 1992, groundwater nitrate levels have risen. Our results warrant greater scholarly and policymaking attention to understand and combat the adverse effects of nitrate.
Inconsistency detection in cancer data classification using explainable-AI
Authors: Mortezaagha Pouria , Rahgozar Arya 
Published: October 2024

AbstractThis paper presents a novel approach to improving text-based cancer data classification by integrating BERTopic clustering with Support Vector Machine (SVM) classifiers, combined with the Explainable Inconsistency Algorithm (EIA). The proposed method leverages advanced preprocessing techniques, including Node2Vec embeddings, to enhance both clustering and classification performance. Through the introduction of EIA, we automatically identify and eliminate outliers and discordant data points, thus improving classification accuracy and providing valuable insights into underlying data relation-ships. A key innovation in this work is the use of recommender systems for mapping clusters to labels, which improves label assignment through collaborative filtering techniques. Our experimental results show a significant increase in both accuracy and F1-score after addressing data inconsistencies, with improvements validated through statistical tests, including t-tests. This paper contributes a robust, explainable, and scalable framework for cancer data analysis, offering potential applications in other domains requiring high-precision text classification. Future work will focus on extending the EIA to other biomedical datasets, optimizing hyperparameters, and deploying the framework in real-time clinical decision-support systems.
Longitudinal modeling of multimorbidity trajectories using large language models
Authors: Yang Lu , Bolton Elliot , Nayar Gowri , Altman Russ B. 
Published: October 2024

ABSTRACTMultimorbidity, the co-occurrence of two or more chronic conditions within an individual, is a major and escalating global health challenge, complicating treatment regimens, straining healthcare resources, and worsening patient outcomes. The complex interplay of shared genetic predispositions, biological pathways, and socioeconomic factors underpins its development, but clinical and research efforts have largely focused on managing diseases in isolation. Understanding multimorbidity trajectories—the accumulation and interaction of chronic diseases over time—is essential to improving preventive strategies and optimizing personalized care. Here, we introduce ForeSITE (Forecasting Susceptibility to Illness with Transformer Embeddings), a novel, transformer-based framework that harnesses advanced machine learning to predict multimorbidity progression. By analyzing longitudinal data from 480,000 participants in the UK Biobank, ForeSITE identifies distinct patterns in the co-occurrence and timing of diseases. Our temporal disease network provides insights into how certain diseases might share common genetic, environmental, or socioeconomic factors, offering more specific guidance for earlier detection and more effective disease management.
The Impact of Clinical and Molecular Variant Properties on Calibration and Performance of Variant Effect Prediction Tools
Authors: Isakov Ofer , Fluss Reut , Marek-Yagel Dina , Ben Shachar Shay 
Published: October 2024

ABSTRACTBackgroundVariant Effect Prediction (VEP) tools are essential for determining the potential pathogenicity of genetic variants, aiding clinical diagnostics and genetic counseling. However, their performance can vary depending on molecular and clinical contexts, complicating variant classification.AimThis study aims to assess the performance variability of commonly used VEP tools under different conditions. Additionally, the study aims to recalibrate score thresholds to better reflect evidence of pathogenicity.MethodsClinVar variants classified as pathogenic (P), likely pathogenic (LP), benign (B), or likely benign (LB) were analyzed using 25 VEP tools. Tools were evaluated based on discriminatory performance. Data were stratified by variant creation date, allele frequency, conservation level, mode of inheritance (MOI), and disease category. For each subset, Bayesian methods were employed to recalibrate score thresholds corresponding to the levels of evidence defined by the American College of Medical Genetics (ACMG).ResultsThe performance of VEP tools varied significantly across different subsets. Variants created after 2020 showed a mild yet significant decrease in the performance of certain VEP tools, particularly those trained on earlier datasets. VEP tools exhibited reduced accuracy for variants with higher allele frequencies, particularly those exceeding a frequency of 10−4, suggesting a need for recalibration when assessing more common variants. Tools demonstrated lower discriminatory performance for variants located in regions with high conservation, mostly due to a decrease in specificity. Variants affecting autosomal recessive (AR) and X-linked (XL) genes were more accurately classified compared to those affecting autosomal dominant (AD) genes by most tools. Differences in MOI and conservation levels within certain disease categories were shown to correlate with overall performance. Recalibration of prediction scores resulted in lower score thresholds in low conservation regions compared to high and uncovered subsets in which higher levels of evidence may be achieved.ConclusionVEP tools exhibit context-dependent performance variability, necessitating score recalibration for accurate classification.
Intellectual disability-causing mutations in KIF11 impair microtubule dynamics and dendritic arborization
Authors: Wingfield Jenna L. , Niese Lukas , Grover Rahul , Diez Stefan , Puthanveettil Sathyanarayanan V 
Published: October 2024

ABSTRACTPrecise control of axonal and dendritic architecture is vital for proper brain function, with microtubule (MT) dynamics playing a central role in this process. Here, we uncover a previously unrecognized function of the molecular motor protein KIF11, which acts as a MT dynamics rheostat in hippocampal neurons to modulate dendritic branching. Known for its role in mitotic spindle bipolarity, KIF11 is also implicated in Microcephaly with or without chorioretinopathy, lymphedema, or intellectual disabilities (MCLID). However, the specific neuronal functions of KIF11 and the impact of its mutations in MCLID have remained largely unexplored. Our studies, using quantitative imaging of MT dynamics following KIF11 inhibition, indicate that KIF11 preferentially binds to parallel MTs in mature neurons. This binding is associated with a marked increase in minus-end-out MT dynamics in both axons and dendrites upon KIF11 loss of function, coupled with enhanced MT flux and extended growth in tertiary dendrites. These changes suggest a novel role for KIF11 in orchestrating dendritic branching. Moreover, introducing MCLID-associated KIF11 mutations, KIF11Y82F, and KIF11ΔCterm, which cause minor microcephaly but severe intellectual disabilities, leads to significantly reduced MT dynamics and impaired dendritic arborization. In a microtubule sliding assay, KIF11Y82Fsignificantly reduced KIF11 velocity while KIF11ΔCtermincreased it. Temporal inhibition of KIF11 using a photo-inhibitable KIF11, show increased MT dynamics and dendritic growth, while activation results in kinked and twisted branches. Together, these data reveal that KIF11 is MT dynamics rheostat and regulator of dendritic arborization in mature neurons and provide new insights into the molecular mechanisms driving MCLID.
Co-cultivating rice plants withAzolla filiculoidesmodifies root architecture and timing of developmental stages
Authors: Cannavò Sara , Paleni Chiara , Costarelli Alma , Valeri Maria Cristina , Cerri Martina , Saccomanno Antonietta , Gregis Veronica , Chini Zittelli Graziella , Dobrev Petre I. , Reale Lara , Kater Martin M. , Paolocci Francesco 
Published: October 2024

AbstractStrategies for increasing the yield of rice, the staple food for more than half of the global population, are needed to keep pace with the expected worldwide population increase, and sustainably forefront the challenges posed by climate change. In Southern-East Asian countries, rice farming benefits from the use ofAzollaspp. for nitrogen supply. In virtue of the symbiosis with the nitrogen-fixing cyanobacteriumTrichormus azollae, Azollaspp. are ferns that release nitrogen into the environment upon decomposition of their biomass. However, if and to what extent actively growingAzollaplants impact on the development of co-cultivated rice plantlets remains to be understood. Here, we show that actively growingAzolla filiculoidesplants alter the architecture of the roots and accelerates the differentiation and proliferation of leaves and tillers in co-cultivated rice plants. These changes result from an intimate cross-talk between rice andA. filiculoides,in which hormones and other metabolites released by the fern in the growth medium trigger an alteration in the rice root transcriptome and the hormonal profiles of both roots and leaves. Overall, the present data let us argue that co-cultivation withA. filiculoidesmight prime rice plants to better deal with both abiotic and biotic stress.HighlightAzolla filiculoidesalters the root transcriptome and hormonal balance in both roots and leaves of co-cultivated rice plantlets, thereby interfering with the progression of their developmental programs
Bacterial Supplements Attenuate Pelvic Irradiation-Induced Brain Metabolic Disruptions via the Gut-Brain Axis: A Multi-Omics Investigation
Authors: Venkidesh Babu Santhi , Narasimhamurthy Rekha Koravadi , Vinay Chigateri M. , Murali Thokur Sreepathy , Mumbrekar Kamalesh Dattaram 
Published: October 2024

AbstractRecent advancements in cancer treatments have increased patient survival rates but also led to treatment-related side effects, negatively impacting the quality of life for cancer survivors. Research has highlighted the crucial role of gut microbiota in overall health, including cognition and neurodegenerative disorders. Cancer patients receiving pelvic radiation often experience gut dysbiosis and this may induce changes in brain through the bi-directional connection between the gut microbiota and the brain, known as the microbiota-gut-brain axis. Bacterial supplements intended to enhance health, whether consumed orally or applied topically. However, the mechanism of bacterial supplements to mitigate pelvic radiation-induced metabolomic alterations is not understood. To investigate this, we employed a multi-omics approach to elucidate how these supplements might mitigate radiation-induced metabolomic changes in the rat brain. A single 6 Gy dose of pelvic radiation was administered to 3–4-month-old Sprague Dawley rats and formulated bacterial supplements were given accordingly. Faecal bacterial sequencing and brain metabolomics performed to identify the changes in the gut microbiota and brain metabolomic analysis to check the altered brain metabolites post pelvic radiation. High-throughput 16S rRNA sequencing revealed significant shifts in bacterial composition, with reduced diversity in the radiation group compared to controls, which was restored in the supplementation groups. Notably, the dominant genera in the radiation group includedMethanobrevibacter, whileParasutterellaandBrachyspirawere prevalent in the supplementation cohorts. Untargeted metabolomic analysis identified 2,554 annotated metabolites, with 56 showing significant differences across groups. Principal Component Analysis demonstrated distinct metabolomic profiles between irradiated and control groups, with specific metabolomic pathways like retinol and glycerophospholipid metabolism altered by irradiation. Bacterial supplementation significantly attenuated these metabolomic disruptions. Therefore, bacterial supplementation could be a promising approach to addressing radiation-induced metabolomic reprogramming in the brains through gut dysbiosis in patients undergoing pelvic radiotherapy, enhancing overall well-being.
Mitochondrial reactive oxygen species cause arrhythmias in hypertrophic cardiomyopathy
Authors: Kohlhaas Michael , Sequeira Vasco , Parikh Shan , Dietl Alexander , Richter Olga , Bay Johannes , Bertero Edoardo , Schwemmlein Julia , Tian Qinghai , Friedrich Felix W. , Flenner Frederik , Nickel Alexander G. , Alscher Felix , Nanadikar Maithily S. , Venkataraman Raghav , Baudenbacher Franz J. , Kappl Reinhard , Johnson Victoria , Roma Leticia Prates , Kasakow Andrej , Hohl Mathias , Laufs Ulrich , Hoth Markus , Katschinski Dörthe M. , Böhm Michael , Lipp Peter , Carrier Lucie , Eschenhagen Thomas , Knollmann Björn C. , Maack Christoph 
Published: October 2024

AbstractHypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease and caused by genetic variants that often increase sarcomeric Ca2+sensitivity. While Ca2+sensitization explains diastolic dysfunction, the genesis of ventricular arrhythmias is unresolved. Here, we show that HCM mutations or pharmacological interventions that increase myofilament Ca2+sensitivity generate bioenergetic mismatch and oxidative stress during β-adrenergic stimulation which provide a trigger and a substrate for arrhythmias. For any given sarcomere shortening that produces work and consumes ATP, less Ca2+stimulates the Krebs cycle to maintain mitochondrial NADH. This reverses the mitochondrial transhydrogenase to regenerate NADH from NADPH, supporting ATP production at the cost of NADPH-dependent antioxidative capacity. The ensuing overflow of reactive oxygen species (ROS) from mitochondria and glutathione oxidation induce spontaneous Ca2+release from the sarcoplasmic reticulum and Ca2+waves, well-defined triggers of arrhythmias. Furthermore, transhydrogenase-dependent ROS formation slows electrical conduction during β-adrenergic stimulationin vivo, providing a substrate for arrhythmias. Chronic treatment with a mitochondrially-targeted ROS scavenger abolishes the arrhythmic burden during β-adrenergic stimulation in HCM micein vivo,while inducing mitochondrial ROS with a redox cycler is sufficient to induce arrhythmias in wild-type animals. These findings may lead to new strategies to prevent sudden cardiac death in patients with HCM.
Pharmacological enhancement of slow-wave activity improves cognition and reduces amyloidosis at an early stage in a mouse model of Alzheimer’s disease
Authors: Kollarik Sedef , Bimbiryte Dorita , Sethi Aakriti , Dias Inês , Moreira Carlos G. , Noain Daniela 
Published: October 2024

AbstractImproving sleep in murine Alzheimer’s disease (AD) is associated with reduced brain amyloidosis. However, the window of opportunity for successful sleep-targeted interventions regarding reduction of pathological hallmarks and related cognitive performance remains poorly characterized. Here, we enhanced slow-wave activity (SWA) during sleep via sodium oxybate (SO) oral administration for 2 weeks at early (6 months old) or moderately late (11 months old) disease stages in Tg2576 mice, and evaluated resulting neuropathology and behavioral performance. We observed that cognitive performance of 6 months old Tg2576 mice significantly improved upon SO treatment, whereas no change was observed in 11 months old mice. Histochemical assessment of amyloid plaques demonstrated that SO-treated 11 months old Tg2576 mice had significantly less plaque burden than placebo-treated ones, whereas ELISA of insoluble protein fractions from 6 months old Tg2576 mice’ brains indicated lower Aβ-42/Aβ-40 ratio in SO-treated group vs. placebo-treated controls. Altogether, our results suggest that SWA-dependent reduction of brain amyloidosis leads to alleviated behavioral impairment in Tg2576 mice only if administered early in the disease course, potentially highlighting the key importance of early sleep-based interventions in clinical cohorts.Significance statementA staggering amount of people worldwide live with AD. Despite extensive efforts from academy and industry, no cure is available to date. Sleep may be a modifiable factor involved in onset, progression and potentially also treatment of AD. However, knowledge regarding important aspects of sleep-targeted treatments is missing, e.g. adequate window of opportunity for their efficacious application, their minimal duration or their effect onto both pathology and cognition. We found that pharmacologically enhanced sleep depth is associated with reduced amyloid neuropathology in AD mice brains at both early- and moderately advanced-stage disease. However, only early-stage disease mice significantly benefited from sleep-enhancing treatment. Our results strongly encourage further mechanistic research and the launch of larger scale preclinical investigations in early AD populations.