bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stimulating prefrontal cortex facilitates training transfer by increasing representational overlap
Authors: Wards Yohan , Ehrhardt Shane E. , Filmer Hannah L. , Mattingley Jason B. , Garner Kelly G. , Dux Paul E. 
Published: November 2023

AbstractDifficulties in multitasking may be the price humans pay for our ability to generalise learning to new tasks. Mitigating these costs through training has been associated with reduced overlap of constituent task representations within a task-related brain network. Transcranial direct current stimulation (tDCS), which can modulate neural activity, has shown promise in generalising training gains. Whether tDCS influences the changes in task-associated representations to produce such training generalisation remains unexplored. Here, we paired prefrontal cortex tDCS with multitasking training, and collected functional magnetic resonance imaging data pre- and post- training. We found that 1mA tDCS enhanced visual search performance, and using machine learning to assess the overlap of brain activity related to the training, show that these generalised gains were predicted by changes in classification accuracy for patterns of frontal, parietal, and cerebellar activity in participants who received left prefrontal cortex stimulation. Thus, prefrontal cortex tDCS interacts with training related changes in task representations, potentially driving the generalisation of learning.
Host signature as major driver of root and rhizosphere core microbiomes that differently affect plant functional traits
Authors: Luo Jipeng , Wang Yuanfan , Zhang Yu , Gao Wenzhe , Liang Yongchao , Zhao He-Ping , Gu Shaohua , Li Tingqiang 
Published: November 2023

AbstractBackgroundPlant can evolve with a core root microbiome that maintains essential functions for host performance. However, the relative importance of plant traits and soil factors on the structure, assembly, co-occurrence networks of the core root microbiomes and their relevance for plant characteristics remain elusive. Here, we investigated how plant species identity and soil environment affect the core bacterial communities in the bulk soil, rhizosphere and root endosphere of four plants with a gradient of Cd/Zn accumulation capacity under controlled and field environments. We further tested on the role of the core bacterial isolates in plant growth and accumulation of metal and nutrients.ResultsWe identified root compartment and plant species rather than environmental parameters as the primary driver of Cd-accumulator root microbiome. Stochastic processes were more important for the assembly of endosphere generalists (58.5%) than rhizosphere counterparts (45.2%), indicating that generalists were more robust to environmental changes. Increasing host selection from epiphytes to endophytes resulted in the existence of the endosphere and rhizosphere generalist core microbiota common to different plants under varying growth environments, highlighting that shared environmental and physiological features of host plants are decisive for core microbiome establishment. Further, endophytic core microbiota conferred greater biotic connectivity within networks and was more important predictors of plant metal accumulation, whereas the rhizosphere cores were more closely linked to plant biomass and nutrient status. The divergent functions of rhizosphere and endosphere core microbes on plant characteristics were also validated by inoculating the synthetic communities comprising bacterial isolates belonging to the core microbiota.ConclusionThis study indicated the pivotal role of plant trait in the assembly of conserved and functionally important core microbiome common to different Cd-accumulators, which brings us closer to manipulating the persistent root microbial associations to accelerate the rejuvenation of metal-disturbed soils through host genetics.
ADNP Modulates SINE B2-Derived CTCF-Binding Sites during Blastocyst Formation in Mouse
Authors: Wang Wen , Gao Rui , Yang Dongxu , Ma Mingli , Zang Ruge , Wang Xiangxiu , Chen Chuan , Chen Jiayu , Kou Xiaochen , Zhao Yanhong , Liu Xuelian , Wang Hong , Gao Yawei , Zhang Yong , Gao Shaorong 
Published: November 2023

AbstractDuring early embryo development, the nuclear factor CTCF plays a vital role in organizing chromatin structure and regulating transcription. Recent studies have examined the establishment of nucleosome profiles around the CTCF motif sites shortly after fertilization. However, the kinetics of CTCF chromatin occupation in pre-implantation embryos have remained unclear. In this study, we utilized CUT&RUN technology to investigate CTCF occupancy in mouse pre-implantation development. Our findings revealed that CTCF begins binding to the genome prior to zygotic genome activation (ZGA), with a preference for CTCF anchored chromatin loops. Although the majority of CTCF occupancy is consistently maintained, we identified a specific set of binding sites enriched in the mouse-specific short-interspersed element (SINE) family B2, which are restricted to the cleavage stages. Notably, our data suggested that the neuroprotective protein ADNP may counteract the stable association of CTCF at SINE B2-derived CTCF-binding sites.
Longitudinal trajectories of the neural encoding mechanisms of speech-sound features during the first year of life
Authors: Puertollano Marta , Ribas-Prats Teresa , Gorina-Careta Natàlia , Ijjou-Kadiri Siham , Arenillas-Alcón Sonia , Mondéjar-Segovia Alejandro , Gómez-Roig María Dolores , Escera Carles 
Published: November 2023

AbstractInfants quickly recognize the sounds of their mother language, perceiving the spectrotemporal acoustic features of speech. However, the underlying neural machinery remains unclear. We used an auditory evoked potential termed frequency-following response (FFR) to unravel the neural encoding maturation for two speech sound characteristics: voice pitch and temporal fine structure. The FFR was elicited by a two-vowel stimulus (/oa/) in a sample of 41 healthy-term neonates, tested at birth and retested at the ages of six and twelve months. Results revealed a reduction in neural phase-locking time to the stimulus envelope from birth to six months, remaining stable thereafter. While neural encoding of voice pitch remained consistent, temporal fine structure encoding matured rapidly from birth to six months, without further improvement from this age onwards. Results highlight the critical importance of the first six months in the maturation of neural encoding mechanisms, crucial for phoneme discrimination during early language acquisition.
Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness
Authors: Chowdhury H. M. A. Mohit , Boult Terrance , Oluwadare Oluwatosin 
Published: November 2023

ABSTRACTThe chromosome is a fundamental component of cell biology, housing DNA that encapsulates hierarchical genetic information. DNA compresses its size by forming loops, and these loop regions contain numerous protein particles, including CTCF, SMC3, H3 histone, and Topologically Associating Domains (TADs). In this study, we conducted a comprehensive study of 22 loop calling methods. Additionally, we have provided detailed insights into the methodologies underlying these algorithms for loop detection, categorizing them into five distinct groups based on their fundamental approaches. Furthermore, we have included critical information such as resolution, input and output formats, and parameters. For this analysis, we utilized the primary and replicate GM12878 Hi-C datasets at 5KB and 10KB resolutions. Our evaluation criteria encompassed various factors, including loop count, reproducibility, overlap, running time, Aggregated Peak Analysis (APA), and recovery of protein-specific sites such as CTCF, H3K27ac, and RNAPII. This analysis offers insights into the loop detection processes of each method, along with the strengths and weaknesses of each, enabling readers to effectively choose suitable methods for their datasets. We evaluate the capabilities of these tools and introduce a novel Biological, Consistency, and Computational robustness score (BCCscore) to measure their overall robustness ensuring a comprehensive evaluation of their performance.
Modelling glioblastoma resistance to temozolomide. Combination of spheroid and mathematical models to simulate cellular adaptation in vitro
Authors: Pérez-Aliacar Marina , Ayensa-Jiménez Jacobo , Ranđelović Teodora , Ochoa Ignacio , Doblaré Manuel 
Published: November 2023

AbstractDrug resistance is one of the biggest challenges in the fight against cancer. In particular, in the case of glioblastoma, the most lethal brain tumour, resistance to temozolomide (the standard of care drug for chemotherapy in this tumour), is one of the main reasons behind treatment failure and hence responsible for the poor prognosis of patients diagnosed with this disease.In this paper, we combine the power of three-dimensional in vitro experiments of treated glioblastoma spheroids with mathematical models of tumour evolution and adaptation. We use a novel approach based on internal variables for modelling the acquisition of resistance to temozolomide that is observed in a group of treated spheroids in the experiments. These internal variables describe the cell’s phenotypic state, which depends on the history of drug exposure and affects cell behaviour. We use model selection to determine the most parsimonious model and calibrate it to reproduce the experimental data, obtaining a high level of agreement between the in vitro and in silico outcomes. A sensitivity analysis is carried out to investigate the impact of each model parameter in the predictions. More importantly, we show the utility of our model for answering biological questions, such as what is the intrinsic adaptation mechanism, or for separating the sensitive and resistant populations. We conclude that the proposed in silico framework, in combination with experiments, can be useful to improve our understanding of the mechanisms behind drug resistance in glioblastoma and to eventually set some guidelines for the design of new treatment schemes.
Increased FAN1 expression by mRNA-LNP attenuates CAG repeat expansion in Huntington patients’ iPSC-derived astrocytes
Authors: Cheng Yung-Chih , Nocula-Lugowska Gosia , Ramirez Julita A. , Fan Xiaoyu , Jin Fang , Jiang Zhihua , Bennett Eric , Li Jin , Hokanson David , Grandhi Sneha , Chen Michelle , Cheng Congsheng , Lin Guan-Yu , Lin Laura , Lepsy Chris , Chaparro-Riggers Javier , Bloom Laird , Morrissey David , Stewart Morag , Tadin-Strapps Marija , Chiang Shian-Huey 
Published: November 2023

ABSTRACTExpansion of repeat sequences within the human genome can lead to disease pathogenesis, such as Huntington’s Disease, primarily affecting the nervous system. Genome-wide association studies (GWAS) of age-at-onset in Huntington’s disease (HD) patients demonstrated DNA mismatch repair (MMR) genes are modifiers of somatic expansion and may be potential therapeutic targets for repeat expansion (RE) disorders. FAN1, a Fanconi anemia-associated nuclease, has been reported as an influencer of repeat expansion in the RE mouse models. Here, we show the first demonstration that FAN1 knock-out in HD patient-derived fibroblasts and results in increased CAG repeat length. We also develop a robust novel cell-based platform using stem cell technology to produce the HD patients’ iPSC-derived astrocytes (iAstro). This platform is a disease-relevant system and has a significantly wider assay window, making it more suitable to assess the effect of gene modulation on CAG repeats. A substantial and exponential increase in repeat instability was exhibited in this HD patient’s iPSC-derived astrocytes platform. Over-expression of FAN1 protein viaFAN1plasmid transfection in this platform reduced CAG repeat instability, suggesting that upregulation of FAN1 protein may have a potential protective effect in CAG repeat expansion for a therapeutic setting. We leveraged the mRNA-LNP modality to enhance FAN1 protein expression and revealed that codon-optimizedFAN1mRNA-LNP robustly prevented increased CAG repeat in HD patients’ iPSC-derived astrocytes platform. The data from these cell-based platforms highlight that FAN1 plays a protective role in attenuating expanded somaticHTTCAG repeats and shed light on new therapeutic directions against repeat expansion disorders.
AttSiOff: A self-attention-based approach on siRNA design with inhibition and off-target effect prediction
Authors: Liu Bin , Yuan Ye , Pan Xiaoyong , Shen Hongbin , Jin Cheng 
Published: November 2023

AbstractMotivationSmall interfering RNA (siRNA) is often used for function study and expression regulation of specific genes, as well as the development of small molecule drugs. Selecting siRNAs with high inhibition and low off-target effects from massive candidates is always a great challenge. Increasing experimentally validated samples prompt the development of machine-learning-based algorithms, including Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Graph Neural Network (GNN). However, these methods still suffer from limited accuracy and poor generalization to design both potent and specific siRNAs.ResultsIn this study, we propose a novel approach for siRNA inhibition and off-target effect prediction, named AttSiOff. It combines self-attention-based siRNA inhibition predictor with an mRNA searching package and an off-target filter. The predictor gives the inhibition score via analyzing the embedding of siRNA and local mRNA sequences, generated from pre-trained RNA-FM model, as well as other meaningful prior-knowledge-based features. Self-attention mechanism can detect potentially decisive features, which may determine the inhibition of siRNA. It captures global and local dependencies more efficiently than normal convolutions. The 10-fold cross-validation results indicate that our model achieves a significant improvement of correlation between prediction and label, compared with all existing methods. And it reaches better performance of generalization and robustness on cross-dataset validation. In addition, the mRNA searching package could find all mature mRNAs for given gene name from GENOMES database, and the off-target filter can calculate the amount of unwanted off-target binding sites, which affects the specificity of siRNA. Experiments on mature siRNA drugs show that our entire framework, AttSioff, have excellent convenience and operability in practical applications.Contactyuanye_auto@sjtu.edu.cnorchengjin520@sjtu.edu.cn.
MIRit: an integrative R framework for the identification of impaired miRNA-mRNA regulatory networks in complex diseases
Authors: Ronchi Jacopo , Foti Maria 
Published: November 2023

BackgroundMicroRNAs are crucial regulators of gene expression that participate in nearly every cellular process. Due to their central role, miRNAs are frequently implicated in the development of pathological conditions, as their dysregulation significantly disrupts normal cellular functioning. Consequently, a thorough characterization of the involvement of dysregulated miRNAs in disturbed pathways is imperative for understanding the mechanisms behind diseases. Nevertheless, the limited availability of analytical methods for joint multi-omic analysis of miRNA-mRNA datasets frequently yields inconclusive and contradictory findings. Specifically, the lack of statistical frame-works designed for integrated analysis of miRNA and mRNA data across biological conditions, as well as the insufficiency of methods suitable for non-sample-matched data, severely restricts the understanding of miRNA networks and the repro-ducibility of the conclusions drawn. To address these limitations, here we present MIRit, an open-source and all-in-one R package that enables integrative multi-omic miRNA analyses using various statistical approaches.ResultsTo showcase MIRit’s capabilities, we evaluated the pipeline on a thyroid cancer dataset, comparing 8 papillary thyroid carcinoma samples to contralateral healthy tissue, as well as on Alzheimer’s disease data, comparing temporal cortex samples from patients to those from healthy individuals. In the first case, MIRit revealed that upregulation of miR-146b-5p and miR-146b-3p caused downregulation of PAX8, resulting in decreased thyroid hormone transcription. In contrast, in the second dataset, MIRit showed that disrupted miRNA-mRNA networks in patients with Alzheimer’s disease impact neuroinflammation, glutamatergic signaling, and neuroprotection. In particular, overexpression of miR-320a-3p may reduce SERPINF1, potentially leading to the accumulation ofAβ1−42fragments.ConclusionsThe adoption of MIRit’s pipeline permits a comprehensive evaluation of perturbed regulatory networks in human diseases through a novel approach for integrative pathway analysis of miRNA-mRNA data. Specifically, MIRit enables the characterization of impaired networks at the molecular level, providing an outstanding advantage in the functional characterization of key dysregulated factors involved in disease pathogenesis and progression. In conclusion, our findings demonstrate the efficacy and usability of MIRit, making it a valuable tool for researchers in the field.
Neuronal calcium spikes enable vector inversion in theDrosophilabrain
Authors: Ishida Itzel G. , Sethi Sachin , Mohren Thomas L. , Abbott L.F. , Maimon Gaby 
Published: November 2023

SummaryA typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ∼180° realignment between the vector encoded in the neuronal population and the fly’s internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-a1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.
Nitrite deteriorates bioreactor performance by reducing growth ofCa.Brocadia sapporoensis instead of inhibiting the anammox activity
Authors: Qiao Xuejiao , Zhang Liyu , Wu Yang , Deng Chunfang , Zhang Yichi , Zhang Xue , Yan Yan , Zhuang Weiqin , Yu Ke 
Published: November 2023

AbstractEffects of nitrite on anammox activities have been of widespread concern. However, the molecular mechanisms of specific microorganisms in anammox systems responding to nitrite remain unexplored. This study investigated the effects of excess nitrite on core metabolism of AnAOB and symbiotic bacteria, and further elucidated the response mechanism of these effects on microbial growth and nitrogen removal performance. Specifically, nitrogen removal process in a continuous-flow anaerobic ammonia oxidation membrane bioreactor completely collapsed when the nitrite concentration reached 243 mg N/L. Integrated meta-omics analyses demonstrated that excess nitrite disrupted the energy metabolism ofCa.Brocadia sapporoensis (AMXB1), reducing the energy available for establishing tolerance. It disrupted cell replication by impairing biosynthesis process of AMXB1, especially DNA replication and the formation of vital cell structures, e.g., cell membrane and cell wall, as well as the cellular protection system, leading to the collapse of the anammox system. In addition, the cross-feeding of glycogen, lipopolysaccharide and amino acid between AMXB1 and symbiotic bacteria was hindered by excess nitrite, which also contributed to the anomalous cell proliferation and metabolism of AMXB1. These findings contribute to our understanding of the ability of anammox consortia to respond to nitrite stress and process stability in engineered ecosystems.HighlightsNO--N concentration of 243 mg N/L caused the performance collapse of a continuous-flow anammox MBR.Excess nitrite likely disrupted the energy metabolism of AMXB1, reducing the energy availability for mitigating nitrite toxicity.The cross-feeding between AMXB1 and symbiotic bacteria was hindered by excess nitrite.The hindrance of cross-feeding was reversed as the concentration of nitrite decreased.Graphical abstract
Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing
Authors: Vattulainen Meri , Smits Jos G.A. , Lima Cunha Dulce , Ilmarinen Tanja , Skottman Heli , Zhou Huiqing 
Published: November 2023

SummaryA comprehensive understanding of the human pluripotent stem cell (hPSC) differentiation process stands as a prerequisite for the development hPSC-based therapeutics. In this study, single-cell RNA-sequencing (scRNA-seq) was performed to decipher the heterogeneity during differentiation of three hPSC lines towards corneal limbal stem cells (LSCs). The scRNA-seq data revealed nine clusters encompassing the entire differentiation process, among which five followed the anticipated differentiation path of LSCs. The remaining four clusters were previously undescribed cell states that were annotated as either mesodermal-like or undifferentiated subpopulations, and their prevalence was hPSC line-dependent. Distinct cluster-specific marker genes identified in this study were confirmed by immunofluorescence analysis and employed to purify hPSC-derived LSCs, which effectively minimized the variation in the line-dependent differentiation efficiency. In summary, scRNA-seq offered molecular insights into the heterogeneity of hPSC-LSC differentiation, allowing a data-driven strategy for consistent and robust generation of LSCs, essential for future advancement toward clinical translation.HighlightshPSCs to LSCs spans epithelial, mesodermal, and undifferentiated cell states.scRNA-seq reveals the cell line-dependent differentiation heterogeneity.ITGA6 and AREG can be used to select pure LSC-like subpopulation.
Transcriptomic Implications of Toxic Effects of Nanoparticles on Metabolic Pathways of Liver Cells
Authors: Erden Tüçer Merve , Tunç Nazlican , Tüçer Suat , Şeker Urartu Özgür Şafak 
Published: November 2023

AbstractWhile nanoparticles find applications in various fields such as cosmetics, drug delivery, and medicine, they also exhibit significant drawbacks. The adverse effects remain inadequately comprehended and necessitate further analysis. This study focuses on assessing the impacts of diverse nanoparticles on HepaRG cell spheroids prior to conducting RNA-Seq analysis, cell viability assays were performed to determine the concentrations of NPs that induce toxicity while maintaining 80% cell viability—a concentration sufficient to cause toxicity without total cell death. To mimic the cellular microenvironment, HepaRG cell spheroids were generated and treated with four distinct nanoparticles of varying sizes. Subsequently, these spheroids underwent RNA-seq analysis to identify specific genes responsive to nanoparticle-induced toxicity. Our findings demonstrate that exposure to nanoparticles substantially modifies gene transcription. Notably, 38 differentially expressed genes were shared across all four types of nanoparticles. These genes were linked to distinct categories of Gene Ontology (GO) terms, thereby clarifying their functions and metabolic pathways through GO and KEGG pathway analyses. Remarkably, processes such as apoptosis, sensitivity to metal ions, hypoxia, and oxidative stress consistently exhibited significant enrichment across all nanoparticle types.Abstract Figure