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Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets. This method adeptly addresses challenges related to cross-dataset modeling by capitalizing on high-dimensional redundant genomic features, analogous to reinforcing building pillars with redundant steel rods. Moreover, it integrates adaptive penalization of feature redundancy on a per-sample basis to prevent score flattening and mitigate overfitting. We then developed a purpose-built R package to implement this method for modeling clinical trial datasets. When applied to genomic datasets for HER2 targeted therapies, iGenSig-Rx model demonstrates consistent and reliable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We anticipate that iGenSig-Rx, as an interpretable class of multi-omics modeling methods, will find broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx .
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Genómica , Neoplasias , Humanos , Genómica/métodos , Neoplasias/genética , Neoplasias/terapia , Medicina de Precisión/métodos , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Programas Informáticos , MultiómicaRESUMEN
Biotic and abiotic interactions shape natural microbial communities. The mechanisms behind microbe-microbe interactions, particularly those protein based, are not well understood. We hypothesize that released proteins with antimicrobial activity are a powerful and highly specific toolset to shape and defend plant niches. We have studied Albugo candida, an obligate plant parasite from the protist Oomycota phylum, for its potential to modulate the growth of bacteria through release of antimicrobial proteins into the apoplast. Amplicon sequencing and network analysis of Albugo-infected and uninfected wild Arabidopsis thaliana samples revealed an abundance of negative correlations between Albugo and other phyllosphere microbes. Analysis of the apoplastic proteome of Albugo-colonized leaves combined with machine learning predictors enabled the selection of antimicrobial candidates for heterologous expression and study of their inhibitory function. We found for three candidate proteins selective antimicrobial activity against Gram-positive bacteria isolated from A. thaliana and demonstrate that these inhibited bacteria are precisely important for the stability of the community structure. We could ascribe the antibacterial activity of the candidates to intrinsically disordered regions and positively correlate it with their net charge. This is the first report of protist proteins with antimicrobial activity under apoplastic conditions that therefore are potential biocontrol tools for targeted manipulation of the microbiome.
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Antiinfecciosos , Arabidopsis , Oomicetos , Parásitos , Animales , Arabidopsis/microbiología , Plantas , Antiinfecciosos/farmacología , Bacterias , Hojas de la Planta/microbiologíaRESUMEN
Triple-negative breast cancer (TNBC) accounts for 10 to 20% of breast cancer, with chemotherapy as its mainstay of treatment due to lack of well-defined targets, and recent genomic sequencing studies have revealed a paucity of TNBC-specific mutations. Recurrent gene fusions comprise a class of viable genetic targets in solid tumors; however, their role in breast cancer remains underappreciated due to the complexity of genomic rearrangements in this cancer. Our interrogation of the whole-genome sequencing data for 215 breast tumors catalogued 99 recurrent gene fusions, 57% of which are cryptic adjacent gene rearrangements (AGRs). The most frequent AGRs, BCL2L14-ETV6, TTC6-MIPOL1, ESR1-CCDC170, and AKAP8-BRD4, were preferentially found in the more aggressive forms of breast cancers that lack well-defined genetic targets. Among these, BCL2L14-ETV6 was exclusively detected in TNBC, and interrogation of four independent patient cohorts detected BCL2L14-ETV6 in 4.4 to 12.2% of TNBC tumors. Interestingly, these fusion-positive tumors exhibit more aggressive histopathological features, such as gross necrosis and high tumor grade. Amid TNBC subtypes, BCL2L14-ETV6 is most frequently detected in the mesenchymal entity, accounting for â¼19% of these tumors. Ectopic expression of BCL2L14-ETV6 fusions induce distinct expression changes from wild-type ETV6 and enhance cell motility and invasiveness of TNBC and benign breast epithelial cells. Furthermore, BCL2L14-ETV6 fusions prime partial epithelial-mesenchymal transition and endow resistance to paclitaxel treatment. Together, these data reveal AGRs as a class of underexplored genetic aberrations that could be pathological in breast cancer, and identify BCL2L14-ETV6 as a recurrent gene fusion in more aggressive form of TNBC tumors.
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Reordenamiento Génico/genética , Proteínas Proto-Oncogénicas c-bcl-2/genética , Proteínas Proto-Oncogénicas c-ets/genética , Proteínas Represoras/genética , Neoplasias de la Mama Triple Negativas/genética , Línea Celular Tumoral , Resistencia a Antineoplásicos/genética , Transición Epitelial-Mesenquimal/genética , Femenino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Fusión Génica/genética , Genómica/métodos , Humanos , Mutación , Neoplasias/tratamiento farmacológico , Neoplasias/genética , Neoplasias/patología , Proteínas de Fusión Oncogénica/genética , Paclitaxel/administración & dosificación , Paclitaxel/efectos adversos , Neoplasias de la Mama Triple Negativas/tratamiento farmacológico , Neoplasias de la Mama Triple Negativas/patología , Secuenciación Completa del Genoma , Proteína ETS de Variante de Translocación 6RESUMEN
k nearest neighbours (kNN) queries are fundamental in many applications, ranging from data mining, recommendation system and Internet of Things, to Industry 4.0 framework applications. In mining, specifically, it can be used for the classification of human activities, iterative closest point registration and pattern recognition and has also been helpful for intrusion detection systems and fault detection. Due to the importance of kNN queries, many algorithms have been proposed in the literature, for both static and dynamic data. In this paper, we focus on exact kNN queries and present a comprehensive survey of exact kNN queries. In particular, we study two fundamental types of exact kNN queries: the kNN Search queries and the kNN Join queries. Our survey focuses on exact approaches over high-dimensional data space, which covers 20 kNN Search methods and 9 kNN Join methods. To the best of our knowledge, this is the first work of a comprehensive survey of exact kNN queries over high-dimensional datasets. We specifically categorise the algorithms based on indexing strategies, data and space partitioning strategies, clustering techniques and the computing paradigm. We provide useful insights for the evolution of approaches based on the various categorisation factors, as well as the possibility of further expansion. Lastly, we discuss some open challenges and future research directions.
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Algoritmos , Minería de Datos , Humanos , Análisis por Conglomerados , Solución de ProblemasRESUMEN
Three-dimensional point cloud registration, which aims to find the transformation that best aligns two point clouds, is a widely studied problem in computer vision with a wide spectrum of applications, such as underground mining. Many learning-based approaches have been developed and have demonstrated their effectiveness for point cloud registration. Particularly, attention-based models have achieved outstanding performance due to the extra contextual information captured by attention mechanisms. To avoid the high computation cost brought by attention mechanisms, an encoder-decoder framework is often employed to hierarchically extract the features where the attention module is only applied in the middle. This leads to the compromised effectiveness of the attention module. To tackle this issue, we propose a novel model with the attention layers embedded in both the encoder and decoder stages. In our model, the self-attentional layers are applied in the encoder to consider the relationship between points inside each point cloud, while the decoder utilizes cross-attentional layers to enrich features with contextual information. Extensive experiments conducted on public datasets prove that our model is able to achieve quality results on a registration task.
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An unprecedented molecular pumping cassette was designed and implemented for the construction of molecular necklaces, that is, radial [n]catenanes. The mechanism was fully confirmed on a model [2]pseudorotaxane, and the novel clipping-followed-by-pumping strategy was used to prepare a series of [n]catenanes (n = 2-5). A pair of [3]catenane diastereomers sequentially threaded with two different wheels was also accomplished. The success of utilizing molecular pumping to construct molecular necklaces offers new insights into complex molecular architectures and expands the application of molecular machines in synthesis.
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BACKGROUND: Silencing of transposable elements (TEs) is essential for maintaining genome stability. Plants use small RNAs (sRNAs) to direct DNA methylation to TEs (RNA-directed DNA methylation; RdDM). Similar mechanisms of epigenetic silencing in the fungal kingdom have remained elusive. RESULTS: We use sRNA sequencing and methylation data to gain insight into epigenetics in the dikaryotic fungus Puccinia graminis f. sp. tritici (Pgt), which causes the devastating stem rust disease on wheat. We use Hi-C data to define the Pgt centromeres and show that they are repeat-rich regions (~250 kb) that are highly diverse in sequence between haplotypes and, like in plants, are enriched for young TEs. DNA cytosine methylation is particularly active at centromeres but also associated with genome-wide control of young TE insertions. Strikingly, over 90% of Pgt sRNAs and several RNAi genes are differentially expressed during infection. Pgt induces waves of functionally diversified sRNAs during infection. The early wave sRNAs are predominantly 21 nts with a 5' uracil derived from genes. In contrast, the late wave sRNAs are mainly 22-nt sRNAs with a 5' adenine and are strongly induced from centromeric regions. TEs that overlap with late wave sRNAs are more likely to be methylated, both inside and outside the centromeres, and methylated TEs exhibit a silencing effect on nearby genes. CONCLUSIONS: We conclude that rust fungi use an epigenetic silencing pathway that might have similarity with RdDM in plants. The Pgt RNAi machinery and sRNAs are under tight temporal control throughout infection and might ensure genome stability during sporulation.
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Basidiomycota , Metilación de ADN , Puccinia , Basidiomycota/genética , Centrómero , Metilación de ADN/genética , Elementos Transponibles de ADN , Inestabilidad Genómica , Humanos , Enfermedades de las Plantas/genética , Puccinia/patogenicidad , ARNRESUMEN
BACKGROUND: Endocrine therapy is the most common treatment for estrogen receptor (ER)-positive breast cancer, but its effectiveness is limited by high rates of primary and acquired resistance. There are likely many genetic causes, and recent studies suggest the important role of ESR1 mutations and fusions in endocrine resistance. Previously, we reported a recurrent ESR1 fusion called ESR1-CCDC170 in 6-8% of the luminal B breast cancers that has a worse clinical outcome after endocrine therapy. Despite being the most frequent ESR1 fusion, its functional role in endocrine resistance has not been studied in vivo, and the engaged mechanism and therapeutic relevance remain uncharacterized. METHODS: The endocrine sensitivities of HCC1428 or T47D breast cancer cells following genetic perturbations of ESR1-CCDC170 were assessed using clonogenic assays and/or xenograft mouse models. The underlying mechanisms were investigated by reverse phase protein array, western blotting, immunoprecipitation, and bimolecular fluorescence complementation assays. The sensitivity of ESR1-CCDC170 expressing breast cancer cells to concomitant treatments of tamoxifen and HER/SRC inhibitors was assessed by clonogenic assays. RESULTS: Our results suggested that different ESR1-CCDC170 fusions endow different levels of reduced endocrine sensitivity in vivo, resulting in significant survival disadvantages. Further investigation revealed a novel mechanism that ESR1-CCDC170 binds to HER2/HER3/SRC and activates SRC/PI3K/AKT signaling. Silencing of ESR1-CCDC170 in the fusion-positive cell line, HCC1428, downregulates HER2/HER3, represses pSRC/pAKT, and improves endocrine sensitivity. More important, breast cancer cells expressing ectopic or endogenous ESR1-CCDC170 are highly sensitive to treatment regimens combining endocrine agents with the HER2 inhibitor lapatinib and/or the SRC inhibitor dasatinib. CONCLUSION: ESR1-CCDC170 may endow breast cancer cell survival under endocrine therapy via maintaining/activating HER2/HER3/SRC/AKT signaling which implies a potential therapeutic strategy for managing these fusion positive tumors.
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Protocolos de Quimioterapia Combinada Antineoplásica/farmacología , Neoplasias de la Mama/genética , Proteínas Portadoras/genética , Resistencia a Antineoplásicos , Receptor alfa de Estrógeno/genética , Proteínas de Fusión Oncogénica , Receptor ErbB-2/metabolismo , Animales , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Línea Celular Tumoral , Dasatinib/administración & dosificación , Femenino , Fulvestrant/administración & dosificación , Humanos , Lapatinib/administración & dosificación , Ratones , Ratones Desnudos , Receptor ErbB-2/antagonistas & inhibidores , Transducción de Señal , Tamoxifeno/administración & dosificación , Ensayos Antitumor por Modelo de Xenoinjerto , Familia-src Quinasas/antagonistas & inhibidores , Familia-src Quinasas/metabolismoRESUMEN
The advent of next generation sequencing technologies has enabled the characterization of the genetic content of entire communities of organisms, including those in clinical specimens, without prior culturing. The MinION from Oxford Nanopore Technologies offers real-time, direct sequencing of long DNA fragments directly from clinical samples. The aim of this study was to assess the ability of unbiased, genome-wide, long-read, shotgun sequencing using MinION to identify Pneumocystis jirovecii directly from respiratory tract specimens and to characterize the associated mycobiome. Pneumocystis pneumonia (PCP) is a life-threatening fungal disease caused by P. jirovecii. Currently, the diagnosis of PCP relies on direct microscopic or real-time quantitative polymerase chain reaction (PCR) examination of respiratory tract specimens, as P. jirovecii cannot be cultured readily in vitro. P. jirovecii DNA was detected in bronchoalveolar lavage (BAL) and induced sputum (IS) samples from three patients with confirmed PCP. Other fungi present in the associated mycobiome included known human pathogens (Aspergillus, Cryptococcus, Pichia) as well as commensal species (Candida, Malassezia, Bipolaris). We have established optimized sample preparation conditions for the generation of high-quality data, curated databases, and data analysis tools, which are key to the application of long-read MinION sequencing leading to a fundamental new approach in fungal diagnostics.
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Metagenómica/métodos , Pneumocystis carinii/clasificación , Pneumocystis carinii/genética , Neumonía por Pneumocystis/diagnóstico , Líquido del Lavado Bronquioalveolar/microbiología , ADN de Hongos , Genoma Fúngico , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Micobioma/genética , Nanoporos , Neumonía por Pneumocystis/microbiología , Reacción en Cadena en Tiempo Real de la Polimerasa , Sistema Respiratorio/microbiología , Sensibilidad y Especificidad , Esputo/microbiologíaRESUMEN
BACKGROUND: Duodenal Diaphragm in adults is very uncommon, caused by congenital and acquired changes. It is reported that acquired duodenal diaphragm is related to the long-term use of nonsteroidal anti-inflammatory drugs. We report an adult presentation of duodenal diaphragm in a 77-year-old woman, suffered from acute cholangitis and choledocholithiasis. She was performed endoscopic retrograde cholangiopancreatography (ERCP) procedure to remove the stone in common bile duct (CBD). After the stenosis ring dilated by endoscopic balloon dilatation, ERCP procedure was applied, and the CBD stone was removed successfully. CONCLUSION: Duodenal diaphragm is difficult to diagnose in clinic. Although the patient in this case had relatively mild symptoms of incomplete upper hemi-abdominal obstruction, these symptoms could be obscured by the emergency acute upper abdominal pain with fever as clinical manifestations of acute cholangitis.
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Colangitis , Coledocolitiasis , Obstrucción Duodenal/cirugía , Anciano , Antiinflamatorios no Esteroideos/efectos adversos , Colangiopancreatografia Retrógrada Endoscópica , Colangitis/diagnóstico por imagen , Colangitis/etiología , Colangitis/cirugía , Coledocolitiasis/diagnóstico por imagen , Coledocolitiasis/cirugía , Conducto Colédoco/diagnóstico por imagen , Conducto Colédoco/cirugía , Dilatación/métodos , Obstrucción Duodenal/etiología , Femenino , HumanosRESUMEN
Genomic data are a powerful tool for elucidating the processes involved in the evolution and divergence of species. The speciation and phylogenetic relationships among Chinese Juglans remain unclear. Here, we used results from phylogenomic and population genetic analyses, transcriptomics, Genotyping-By-Sequencing (GBS), and whole chloroplast genomes (Cp genome) data to infer processes of lineage formation among the five native Chinese species of the walnut genus (Juglans, Juglandaceae), a widespread, economically important group. We found that the processes of isolation generated diversity during glaciations, but that the recent range expansion of J. regia, probably from multiple refugia, led to hybrid formation both within and between sections of the genus. In southern China, human dispersal of J. regia brought it into contact with J. sigillata, which we determined to be an ecotype of J. regia that is now maintained as a landrace. In northern China, walnut hybridized with a distinct lineage of J. mandshurica to form J. hopeiensis, a controversial taxon (considered threatened) that our data indicate is a horticultural variety. Comparisons among whole chloroplast genomes and nuclear transcriptome analyses provided conflicting evidence for the timing of the divergence of Chinese Juglans taxa. J. cathayensis and J. mandshurica are poorly differentiated based our genomic data. Reconstruction of Juglans evolutionary history indicate that episodes of climatic variation over the past 4.5 to 33.80 million years, associated with glacial advances and retreats and population isolation, have shaped Chinese walnut demography and evolution, even in the presence of gene flow and introgression.
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Especiación Genética , Genoma del Cloroplasto , Genómica , Hibridación Genética , Juglans/genética , Filogenia , Análisis de Secuencia de ADN , Transcriptoma/genética , China , Genética de Población , Técnicas de Genotipaje , Geografía , Haplotipos/genética , Polimorfismo de Nucleótido Simple/genéticaAsunto(s)
Basidiomycota , Australia , Basidiomycota/genética , Cromosomas , Enfermedades de las Plantas , PucciniaRESUMEN
Gene fusions have long been considered principally as the oncogenic events of hematologic malignancies, but have recently gained wide attention in solid tumors due to several milestone discoveries and the advancement of deep sequencing technologies. With the progress in deep sequencing studies of breast cancer transcriptomes and genomes, the discovery of recurrent and pathological gene fusions in breast cancer is on the focus. Recently, driven by new deep sequencing studies, several recurrent or pathological gene fusions have been identified in breast cancer, including ESR1-CCDC170, SEC16A-NOTCH1, SEC22B-NOTCH2, and ESR1-YAP1 etc. More important, most of these gene fusions are preferentially identified in the more aggressive breast cancers, such as luminal B, basal-like, or endocrine-resistant breast cancer, suggesting recurrent gene fusions as additional key driver events in these tumors other than the known drivers such as the estrogen receptor. In this paper, we have comprehensively summarized the newly identified recurrent or pathological gene fusion events in breast cancer, reviewed the contributions of new genomic and deep sequencing technologies to new fusion discovery and the integrative bioinformatics tools to analyze these data, highlighted the biological relevance and clinical implications of these fusion discoveries, and discussed future directions of gene fusion research in breast cancer.
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Neoplasias de la Mama/patología , Fusión Génica , Genómica/métodos , Neoplasias de la Mama/genética , Femenino , Perfilación de la Expresión Génica , Predisposición Genética a la Enfermedad , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Análisis de Secuencia de ADNRESUMEN
Small ubiquitin-like modifier (SUMO) proteins act in DNA double-strand break (DSB) repair, but the pathway specificity of the three major isoforms has not been defined. In experiments in which we depleted the endogenous SUMO protein by RNAi, we found that SUMO1 functioned in all subpathways of either homologous recombination (HR) or non-homologous end joining (NHEJ), whereas SUMO2/3 was required for the major NHEJ pathway, called conservative NHEJ, but dispensable in other DSB repair pathways. To our surprise, we found that depletion of UBC9, the unique SUMO E2 enzyme, had no effect in HR or alternative NHEJ (Alt-NHEJ) but was required for conservative NHEJ. Consistent with this result, both non-conjugatable mutant and wild-type SUMO1 proteins functioned similarly in HR and Alt-NHEJ. These results detail the functional roles of specific SUMO isoforms in DSB repair in mammalian cells and reveal that SUMO1 functions in HR or Alt-NHEJ as a free protein and not as a protein conjugate.
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Daño del ADN , Reparación del ADN , Isoformas de Proteínas/fisiología , Proteínas Modificadoras Pequeñas Relacionadas con Ubiquitina/fisiología , Secuencia de Bases , Isoformas de Proteínas/genética , Interferencia de ARN , ARN Interferente Pequeño/genética , Proteínas Modificadoras Pequeñas Relacionadas con Ubiquitina/genéticaRESUMEN
This paper reviews the current research progress in the application of Artificial Intelligence (AI) based on ischemic stroke imaging, analyzes the main challenges, and explores future research directions. This study emphasizes the application of AI in areas such as automatic segmentation of infarct areas, detection of large vessel occlusion, prediction of stroke outcomes, assessment of hemorrhagic transformation risk, forecasting of recurrent ischemic stroke risk, and automatic grading of collateral circulation. The research indicates that Machine Learning (ML) and Deep Learning (DL) technologies have tremendous potential for improving diagnostic accuracy, accelerating disease identification, and predicting disease progression and treatment responses. However, the clinical application of these technologies still faces challenges such as limitations in data volume, model interpretability, and the need for real-time monitoring and updating. Additionally, this paper discusses the prospects of applying large language models, such as the transformer architecture, in ischemic stroke imaging analysis, emphasizing the importance of establishing large public databases and the need for future research to focus on the interpretability of algorithms and the comprehensiveness of clinical decision support. Overall, AI has significant application value in the management of ischemic stroke; however, existing technological and practical challenges must be overcome to achieve its widespread application in clinical practice.
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Background: Brain metastases present significant challenges in radiotherapy due to the need for precise tumor delineation. Traditional methods often lack the efficiency and accuracy required for optimal treatment planning. This paper proposes an improved U-Net model that uses a position attention module (PAM) for automated segmentation of gross tumor volumes (GTVs) in computed tomography (CT) simulation images of patients with brain metastases to improve the efficiency and accuracy of radiotherapy planning and segmentation. Methods: We retrospectively collected CT simulation imaging datasets of patients with brain metastases from two centers, which were designated as the training and external validation datasets. The U-Net architecture was enhanced by incorporating a PAM into the transition layer, which improved the automated segmentation capability of the U-Net model. With cross-entropy loss employed as the loss function, the samples from the training dataset underwent training. The model's segmentation performance on the external validation dataset was assessed using metrics including the Dice similarity coefficient (DSC), intersection over union (IoU), accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and Hausdorff distance (HD). Results: The proposed automated segmentation model demonstrated promising performance on the external validation dataset, achieving a DSC of 0.753±0.172. In terms of evaluation metrics (including the DSC, IoU, accuracy, sensitivity, MCC, and HD), the model outperformed the standard U-Net, which had a DSC of 0.691±0.142. The proposed model produced segmentation results that were closer to the ground truth and could reveal more detailed features of brain metastases. Conclusions: The PAM-improved U-Net model offers considerable advantages in the automated segmentation of the GTV in CT simulation images for patients with brain metastases. Its superior performance in comparison with the standard U-Net model supports its potential for streamlining and improving the accuracy of radiotherapy. With its ability to produce segmentation results consistent with the ground truth, the proposed model holds promise for clinical adoption and provides a reference for radiation oncologists to make more informed GTV segmentation decisions.
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Cerium oxide nanoparticles (CeNPs) have emerged as a potent therapeutic agent in the realm of wound healing, attributing their efficacy predominantly to their exceptional antioxidant properties. Mimicking the activity of endogenous antioxidant enzymes, CeNPs alleviate oxidative stress and curtail the generation of inflammatory mediators, thus expediting the wound healing process. Their application spans various disease models, showcasing therapeutic potential in treating inflammatory responses and infections, particularly in oxidative stress-induced chronic wounds such as diabetic ulcers, radiation-induced skin injuries, and psoriasis. Despite the promising advancements in laboratory studies, the clinical translation of CeNPs is challenged by several factors, including biocompatibility, toxicity, effective drug delivery, and the development of multifunctional compounds. Addressing these challenges necessitates advancements in CeNP synthesis and functionalization, novel nano delivery systems, and comprehensive bio effectiveness and safety evaluations. This paper reviews the progress of CeNPs in wound healing, highlighting their mechanisms, applications, challenges, and future perspectives in clinical therapeutics.
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Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.
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Visual imagery allows for the construction of rich internal experience in our mental world. However, it has remained poorly understood how imagery experience derives volitionally as opposed to being cue driven. Here, using electroencephalography and functional magnetic resonance imaging, we systematically investigate the spatiotemporal dynamics of self-generated imagery by having participants volitionally imagining one of the orientations from a learned pool. We contrast self-generated imagery with cue-induced imagery, where participants imagined line orientations based on associative cues acquired previously. Our results reveal overlapping neural signatures of cue-induced and self-generated imagery. Yet, these neural signatures display substantially differential sensitivities to the two types of imagery: self-generated imagery is supported by an enhanced involvement of the anterior cortex in representing imagery contents. By contrast, cue-induced imagery is supported by enhanced imagery representations in the posterior visual cortex. These results jointly support a reverse cortical hierarchy in generating and maintaining imagery contents in self-generated versus externally cued imagery.
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Señales (Psicología) , Corteza Visual , Humanos , Imaginación , Imagen por Resonancia Magnética/métodos , Electroencefalografía/métodos , Mapeo EncefálicoRESUMEN
Genetic and epigenetic changes after polyploidization events could result in variable gene expression and modified regulatory networks. Here, using large-scale transcriptome data, we constructed co-expression networks for diploid, tetraploid, and hexaploid wheat species, and built a platform for comparing co-expression networks of allohexaploid wheat and its progenitors, named WheatCENet. WheatCENet is a platform for searching and comparing specific functional co-expression networks, as well as identifying the related functions of the genes clustered therein. Functional annotations like pathways, gene families, protein-protein interactions, microRNAs (miRNAs), and several lines of epigenome data are integrated into this platform, and Gene Ontology (GO) annotation, gene set enrichment analysis (GSEA), motif identification, and other useful tools are also included. Using WheatCENet, we found that the network of WHEAT ABERRANT PANICLE ORGANIZATION 1 (WAPO1) has more co-expressed genes related to spike development in hexaploid wheat than its progenitors. We also found a novel motif of CCWWWWWWGG (CArG) specifically in the promoter region of WAPO-A1, suggesting that neofunctionalization of the WAPO-A1 gene affects spikelet development in hexaploid wheat. WheatCENet is useful for investigating co-expression networks and conducting other analyses, and thus facilitates comparative and functional genomic studies in wheat. WheatCENet is freely available at http://bioinformatics.cpolar.cn/WheatCENet and http://bioinformatics.cau.edu.cn/WheatCENet.