bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid, Non-Invasive Breath Analysis for Enhancing Detection of Silicosis Using Mass Spectrometry and Interpretable Machine Learning
Authors: Baker Merryn J , Gordon Jeff , Thiruvarudchelvan Aruvi , Yates Deborah , Donald William A 
Published: October 2024

AbstractOccupational lung diseases, such as silicosis, are a significant global health concern, especially with increasing exposure to engineered stone dust. Early detection of silicosis is helpful for preventing disease progression, but existing diagnostic methods, including X-rays, CT scans, and spirometry, often detect the disease only at late stages. This study investigates a rapid, non-invasive diagnostic approach using atmospheric pressure chemical ionization-mass spectrometry (APCI-MS) to analyse volatile organic compounds (VOCs) in exhaled breath from 31 silicosis patients and 60 healthy controls. Six different interpretable machine learning (ML) models with Shapley additive explanations (SHAP) were applied to classify these samples and determine VOC features that contribute the most significantly to model accuracy. The extreme gradient boosting (XGB) classifier demonstrated the best performance, achieving an area under the receiver-operator characteristic curve of 0.933 with the top ten SHAP features. Them/z442 feature, potentially corresponding to leukotriene-E3, emerged as a significant predictor for silicosis. The VOC sampling and measurement process takes less than five minutes per sample, highlighting its potential suitability for large-scale population screening. Moreover, the ML models are interpretable through SHAP, providing insights into the features contributing to the model’s predictions. This study suggests that APCI-MS breath analysis could enable early and non-invasive diagnosis of silicosis, helping to improve disease outcomes.
Hydroxyzine in Acute Hypertension: A Cohort Study
Authors: Nożewski Jakub , Remiszewski Piotr , Filipek Kinga , Pisklak Agata , Abramczyk Aleksandra , Pyzel Stanisław , Śliż Daniel 
Published: October 2024

AbstractCaptopril, an ACE inhibitor, is widely used for acute hypertensive episodes, while hydroxyzine, an antihistamine with sedative and anxiolytic effects, is also employed in Poland despite limited research on its efficacy for this purpose. To our knowledge, no prior studies have specifically investigated the direct impact of hydroxyzine on hypertension, despite its common use in Polish medical practice.A retrospective cohort analysis of 2144 patients who required emergency intervention for hypertension or had high blood pressure during other interventions. Effectiveness was based on blood pressure improvement post-intervention.84.28% of interventions were performed by basic emergency teams, and 15.72% by specialist teams. Captopril and hydroxyzine were the most commonly used medications. Blood pressure improved in 36.61% of patients, with no improvement in 41.47%. Hydroxyzine was more frequently administered by paramedic teams, while captopril was favoured by specialist teams. There were no statistically significant differences in captopril use across age groups, with approximately 80% receiving it. Hydroxyzine use did not vary significantly by age, though its overall use was low. Hydroxyzine showed a non-significant trend towards greater blood pressure reduction compared to captopril.Captopril is the primary treatment for acute hypertension in emergency settings, but hydroxyzine may have potential benefits, especially in patients with anxiety-related hypertension. However, due to the lack of significant evidence and current guidelines advising against hydroxyzine in elderly patients, further research is needed to establish protocols and optimize hypertension treatment strategies. Additionally, incorporating anxiolytics into guidelines and an official statement on their use would aid clinical practice.
Introducing Haptic Feedback in Real-Time fMRI Neurofeedback: A Novel Approach to Modulate Primary Motor Cortex Activity
Authors: Fleury Mathis , Cloerec Pauline , Duche Quentin , Lioi Giulia , Lécuyer Anatole 
Published: October 2024

ABSTRACTAs fMRI-Neurofeedback (fMRI-NF) is still in its early stages, many questions remain regarding the optimal methodology, particularly in relation to feedback modalities. One of the core components of neurofeedback is the feedback itself, which the participant relies on to regulate, learn, and refine their mental strategies. However, most fMRI-NF protocols to date have primarily used visual feedback, which may not be ideal in all cases. Certain individuals or populations might benefit from alternative or additional feedback modalities, such as haptic feedback —a novel approach in this field— along with auditory, virtual reality/immersive environments, or a combination of these. In this study, we assess the performance of neurofeedback elicited by a motor imagery (MI) task using visuo-haptic feedback and compare it to unisensory visual and haptic feedback. Our results suggest that combining visual and haptic feedback in neurofeedback may be more engaging than conventional visual feedback alone, particularly in neurorehabilitation, by more effectively activating the primary motor cortex—a region considered a key target for promoting motor recovery.
The solute carrier superfamily interactome
Authors: Frommelt Fabian , Ladurner Rene , Goldmann Ulrich , Wolf Gernot , Ingles-Prieto Alvaro , Lineiro-Retes Eva , Gelová Zuzana , Hopp Ann-Katrin , Christodoulaki Eirini , Teoh Shao Thing , Leippe Philipp , Rebsamen Manuele , Lindinger Sabrina , Serrano Iciar , Onstein Svenja , Klimek Christoph , Barbosa Barbara , Pantielieieva Anastasiia , Dvorak Vojtech , Hannich J. Thomas , Schoenbett Julian , Sansig Gilles , Mocking Tamara A.M. , Ooms Jasper F. , IJzerman Adriaan P. , Heitman Laura H. , Sykacek Peter , Reinhardt Juergen , Müller André C , Wiedmer Tabea , Superti-Furga Giulio 
Published: October 2024

AbstractSolute carrier (SLC) transporters form a protein superfamily that enables transmembrane transport of diverse substrates including nutrients, ions and drugs. There are about 450 different SLCs, residing in a variety of subcellular membranes. Loss-of-function of an unusually high proportion of SLC transporters is genetically associated with a plethora of human diseases, making SLCs a rapidly emerging but challenging drug target class. Knowledge of their protein environment may elucidate the molecular basis for their functional integration with metabolic and cellular pathways and help conceive pharmacological interventions based on modulating proteostatic regulation. We aimed at obtaining a global survey of the SLC protein interaction landscape and mapped the protein-protein interactions of 396 SLCs by interaction proteomics. We employed a functional assessment based on RNA interference of interactors in combination with measurement of protein stability and localization. As an example, we detail the role of a SLC16A6 phospho-degron, and the contributions of PDZ-domain proteins LIN7C and MPP1 to the trafficking of SLC43A2. Overall, our work offers a resource for SLC-protein interactions for the scientific community.
Enhanced prediction of protein functional identity through the integration of sequence and structural features
Authors: Fujita Suguru , Terada Tohru 
Published: October 2024

AbstractAlthough over 300 million protein sequences are registered in a reference sequence database, only 0.2% have experimentally determined functions. This suggests that many valuable proteins, potentially catalyzing novel enzymatic reactions, remain undiscovered among the vast number of function-unknown proteins. In this study, we developed a method to predict whether two proteins catalyze the same enzymatic reaction by analyzing sequence and structural similarities, utilizing structural models predicted by AlphaFold2. We performed pocket detection and domain decomposition for each structural model. The similarity between protein pairs was assessed using features such as full-length sequence similarity, domain structural similarity, and pocket similarity. We developed several models using conventional machine learning algorithms and found that the LightGBM-based model outperformed the models. Our method also surpassed existing approaches, including those based solely on full-length sequence similarity and state-of-the-art deep learning models. Feature importance analysis revealed that domain sequence identity, calculated through structural alignment, had the greatest influence on the prediction. Therefore, our findings demonstrate that integrating sequence and structural information improves the accuracy of protein function prediction.
SAMURAI: Shallow Analysis of copy nuMber alterations Using a Reproducible And Integrated bioinformatics pipeline
Authors: Potente Sara , Boscarino Diego , Paladin Dino , Marchini Sergio , Beltrame Luca , Romualdi Chiara 
Published: October 2024

AbstractShallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner.SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data pre-processing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g., circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses.To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios.By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.
RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets
Authors: Hemm Luisa , Rabsch Dominik , Ropp Halie R. , Reimann Viktoria , Gerth Philip , Bartel Jürgen , Brenes-Álvarez Manuel , Maaß Sandra , Becher Dörte , Hess Wolfgang R. , Backofen Rolf 
Published: October 2024

AbstractThe computational analysis of large proteomics datasets, such as those from gradient profiling or spatially resolved proteomics, is often as crucial as the experimental design. We present RAPDOR, a tool for intuitive analyzing and visualizing such datasets, based on the Jensen-Shannon distance and subsequent analysis of similarities between replicates, applied to three datasets. First, we examined the in-gradient distribution profiles of protein complexes with or without RNase treatment (GradR) to identify the set of RNA-binding proteins (RBPs) in the cyanobacteriumSynechocystissp. PCC 6803. RBPs play pivotal regulatory and structural roles; although numerous RBPs have been identified, the complete set is unknown for any species. RAPDOR identified 80 potential RBPs, including ribosomal proteins, likely RNA-modifying enzymes, and several proteins not previously associated with RNA binding. High-ranking putative RBPs, such as the universal stress protein Sll1388, or the translation inhibitor LrtA/RaiA, were predicted by RAPDOR but not the TriPepSVM algorithm, indicating uncharacterized RBP domains. These data are available online athttps://synecho-rapdor.biologie.uni-freiburg.de, providing a comprehensive resource for RNase-sensitive protein complexes in cyanobacteria. We then show by reanalyzing existing datasets, that RAPDOR is effective in examining the intracellular redistribution of proteins under stress conditions. RAPDOR is a generic, non-parametric tool for the intuitive and versatile analysis of highly complex data sets such as the study of protein distributions using fractionation protocols.
Deciphering shared molecular dysregulation across Parkinson’s Disease variants using a multi-modal network-based data integration and analysis
Authors: Zagare Alise , Balaur Irina , Rougny Adrien , Saraiva Claudia , Gobin Matthieu , Monzel Anna S. , Ghosh Soumyabrata , Satagopam Venkata P. , Schwamborn Jens C. 
Published: October 2024

AbstractParkinson’s disease (PD) is a progressive neurodegenerative disorder with no effective treatment. Advances in neuroscience and systems biomedicine now enable the use of complex patient-specificin vitrodisease models and cutting-edge computational tools for data integration, enhancing our understanding of complex PD mechanisms. To explore common biomedical features across monogenic PD forms, we developed a knowledge graph (KG) by integrating previously published high-content imaging and RNA sequencing data of PD patient-specific midbrain organoids harbouring LRRK2-G2019S, SNCA triplication, GBA-N370S or MIRO1-R272Q mutations with publicly available biological data. Furthermore, we generated a single-cell RNA sequencing dataset of midbrain organoids derived fromidiopathic PD patients (IPD) to stratify IPD patients towards genetic forms of PD. Despite high PD heterogeneity, we found that common transcriptomic dysregulation in monogenic PD forms is reflected in IPD glial cells. In addition, dysregulation in ROBO signalling might be involved in shared pathophysiology between monogenic PD and IPD cases.
CXXC-finger protein 1 associates with FOXP3 to stabilize homeostasis and suppressive functions of regulatory T cells
Authors: Meng Xiaoyu , Zhu Yezhang , Liu Kuai , Wang Yuxi , Liu Xiaoqian , Liu Chenxin , Zeng Yan , Wang Shuai , Gao Xianzhi , Shen Xin , Chen Jing , Tao Sijue , Xu Qianying , Dong Linjia , Shen Li , Wang Lie 
Published: October 2024

AbstractFOXP3-expressing regulatory T (Treg) cells play a pivotal role in maintaining immune homeostasis and tolerance, with their activation being crucial for preventing various inflammatory responses. However, the mechanisms governing the epigenetic program in Tregcells during their dynamic activation remain unclear. In this study, we demonstrate that CXXC finger protein 1 (CXXC1) interacts with the transcription factor FOXP3 and facilitates the regulation of target genes by modulating H3K4me3 deposition.Cxxc1deletion in Tregcells leads to severe inflammatory disease and spontaneous T-cell activation, with impaired immunosuppressive function. As a transcriptional regulator, CXXC1 promotes the expression of key Tregfunctional markers under steady-state conditions, which are essential for the maintenance of Tregcell homeostasis and their suppressive functions. Epigenetically, CXXC1 binds to the genomic regulatory regions of Tregprogram genes in mouse Tregcells, overlapping with FOXP3 binding sites. Given its critical role in Tregcell homeostasis, CXXC1 presents itself as a promising therapeutic target for autoimmune diseases.
Sex-specific role of epigenetic modification of a leptin upstream enhancer in the adipose tissue
Authors: Müller Luise , Oelkrug Rebecca , Mittag Jens , Hoffmann Anne , Ghosh Adhideb , Noé Falko , Wolfrum Christian , Jurado Esther Guiu , Klöting Nora , Dietrich Arne , Blüher Matthias , Kovacs Peter , Krause Kerstin , Keller Maria 
Published: October 2024

AbstractObjectiveMaternal hormonal status can have long-term effects on offspring metabolic health, likely regulated via epigenetic mechanisms. We elucidated the effect of maternal thyroid hormones on epigenetic regulation ofLeptin(Lep) transcription in adipose tissue (AT) and investigated the role of DNA methylation at aLepupstream enhancer (UE) in adipocyte biology.MethodsPregnant mice were treated with Triiodothyronine (T3). Offspring body composition and adipose tissue were analysed at 6 months (treatment:N= 8, control:N= 12). DNA methylation at theLepUE andLepmRNA levels in gonadal white adipose tissue (gWAT) and leptin serum levels were measured. TheLepUE was hypomethylated in murine preadipocytes using a dCas9-SunTag-TET1 system, followed by differentiation. In human visceral AT samples (N= 52) from the Leipzig Obesity BioBank (LOBB)LEPUE methylation andLEPmRNA levels were assessed alongside leptin serum levels and correlated with body fat percentage. Causal relationships were explored using mediation analysis.ResultsHigh maternal T3 levels reduced offspring body weight, total fat, and gWAT mass. Female offspring of T3-treated mothers showed lowerLepmRNA levels and higherLepUE methylation compared to controls. CRISPR/dCas9 editing reducedLepUE methylation by ∼20% in preadipocytes without alteringLepexpression or lipid accumulation after differentiation. In humans, a mediation of sex-specific difference in body fat percentage viaLepUE methylation was found.ConclusionMaternal thyroid hormones might affect offspring gWATLepexpression in a sex-specific manner, potentially driven by DNA methylation at theLepUE, influencing body fat percentage.
Experience in developing the human genome standard E701
Authors: Vasiliadis Iuliia , Belova Vera , Shmitko Anna , Kuznetsova Anna , Samitova Alina , Suchalko Oleg , Goltsov Andrey , Shatalov Peter , Shegai Peter , Melkova Olga , Kulyabina Tatiana , Kulyabina Elena , Rebrikov Denis , Korostin Dmitriy 
Published: October 2024

AbstractThe first Russian human genome standard E701 was developed through a collaborative research involving four laboratories: Pirogov Russian National Research Medical University, National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I.Kulakov, National Research Center Kurchatov Institute, and National Medical Research Radiological Centre. Whole-genome sequencing of short reads on various platforms (MGI Tech, Illumina) and alignment to the reference human genome GRCh38.p14 were performed for the E701 sample. Subsequently, 3842877 high confidence genomic variants were identified, which can be used as a standard for calculating statistical quality metrics while analyzing sequencing data. Furthermore, 9096 biallelic variants were identified on the autosomes and the X chromosome, with a minor allele frequency exceeding 0.4. Additionally, mitochondrial DNA sequencing was performed with the breadth of coverage over 99.9% at 1000X.
Dopamine activity encodes the changing valence of the same stimulus in conditioned taste aversion paradigms
Authors: Loh Maxine K. , Hurh Samantha , Bazzino Paula , Donka Rachel M. , Keinath Alexandra T. , Roitman Jamie D. , Roitman Mitchell F. 
Published: October 2024

ABSTRACTMesolimbic dopamine encoding of non-contingent rewards and reward-predictive cues has been well established. Considerable debate remains over how mesolimbic dopamine responds to aversion and in the context of aversive conditioning. Inconsistencies may arise from the use of aversive stimuli that are transduced along different neural paths relative to reward or the conflation of responses to avoidance and aversion. Here, we made intraoral infusions of sucrose and measured how dopamine and behavioral responses varied to the changing valence of sucrose. Pairing intraoral sucrose with malaise via injection of lithium chloride (LiCl) caused the development of a conditioned taste aversion (CTA), which rendered the typically rewarding taste of sucrose aversive upon subsequent re-exposure. Following CTA formation, intraoral sucrose suppressed the activity of ventral tegmental area dopamine neurons (VTADA) and nucleus accumbens (NAc) dopamine release. This pattern of dopamine signaling after CTA is similar to intraoral infusions of innately aversive quinine and contrasts with that to sucrose when it was novel or not paired with LiCl. Dopamine responses were negatively correlated with behavioral reactivity to intraoral sucrose and predicted home cage sucrose preference. Further, dopamine responses scaled with the strength of the CTA, which was increased by repeated LiCl pairings and weakened through extinction. Thus, the findings demonstrate differential dopamine encoding of the same taste stimulus according to its valence, which is aligned to distinct behavioral responses.
Enhanced kinase translocation reporters for simultaneous real-time measurement of PKA, ERK, and Ca2+
Authors: Tsai Shang-Jui , Gong Yijing , Dabbs Austin , Zahra Fiddia , Xu Junhao , Geske Aleksander , Caterina Michael J. , Gould Stephen J. 
Published: October 2024

ABSTRACTKinase translocation reporters (KTRs) are powerful tools for single-cell measurement of time-integrated kinase activity but suffer from restricted dynamic range and limited sensitivity, particularly in neurons. To address these limitations, we developed enhanced KTRs (eKTRs) for protein kinase A (PKA) and extracellular signal-regulated kinase (ERK) that display high sensitivity, rapid response kinetics, broad dynamic range, cell type-specific tuning, and an ability to detect PKA and ERK activity in primary sensory neurons. Moreover, co-expression of optically separable eKTRs for PKA and ERK revealed the kinetics of expected and unexpected crosstalk between PKA, ERK, protein kinase C, and calcium signaling pathways, demonstrating the utility of eKTRs for live cell monitoring of diverse and interacting signaling pathways. These results open the door to improved live-cell and in vivo measurements of key signaling pathways in neurons, while at the same time demonstrating the importance of KTR size and NLS strength to KTR dynamics.
Posterior parietal cortex regulates neural timescales and stimulus-driven attentional modulation in the prefrontal cortex
Authors: Soyuhos Orhan , Moore Tirin , Chaudhuri Rishidev , Chen Xiaomo 
Published: October 2024

AbstractIntrinsic neural timescales characterize the dynamics of endogenous fluctuations in neural activity. We measured the intrinsic timescales of prefrontal neurons and examined their changes during posterior parietal cortex (PPC) inactivation. Frontal eye field (FEF) neurons within the prefrontal cortex (PFC) exhibited a bimodal distribution of timescales: short-timescale neurons showed stronger transient visual responses, while long-timescale neurons exhibited stronger sustained modulation during stimulus-driven attention. PPC inactivation increased intrinsic timescales in both neuron types, with a 15-fold greater increase in short-timescale neurons. Additionally, it reduced visual and attentional modulation, particularly impairing attentional modulation in long-timescale neurons. Our results provide the first causal evidence that the intrinsic timescales of FEF neurons depend on PPC and suggest the presence of at least two network motifs with distinct timescales that contribute to neuronal dynamics and functional computations within FEF. The heterogeneity in these timescales may facilitate cognitive flexibility, allowing PFC to adapt to varying task demands.