Search Results (392)

The impairment of neural crest cells (NCCs) plays a pivotal role in the pathogenesis of fetal alcohol spectrum disorders (FASD). Epigenetic regulators mediate ethanol-induced disruptions in NCC development and represent promising targets for nutritional interventions. Here, we developed a biologically informed machine learning framework to predict nutritional supplements that modulate five key epigenetic regulators (miR-34a, DNMT3a, HDAC, miR-125b, and miR-135a) and mitigate ethanol’s adverse effects on NCCs. The optimized models demonstrated robust predictive performance and identified a number of nutritional supplements that could attenuate ethanol-induced NCC impairment, including resveratrol, vitamin B12, emodin, quercetin, and broccoli sprout-derived compounds. Our optimized models also revealed structural features that are critical for mitigating ethanol-induced NCC impairment through specific epigenetic mechanisms. These findings support predictive modeling as a tool to prioritize nutritional supplements for further investigation and the development of dietary strategies to prevent or reduce the risk of FASD. Full article

Accurate identification of lithology is considered very important in oil and gas exploration because it has a direct impact on the evaluation and development planning of any reservoir. In complex reservoirs where extreme class imbalance occurs, as critical minority lithologies cover less than 5%, the identification accuracy is severely constrained. Recent deep learning methods include convolutional neural networks, recurrent architectures, and transformer-based models that have achieved substantial improvements over traditional machine learning approaches in identifying lithology. These methods demonstrate great performance in catching spatial patterns and sequential dependencies from well log data, and they show great recognition accuracy, up to 85–88%, in the case of a moderate imbalance scenario. However, when these methods are extended to complex reservoirs under extreme class imbalance, the following three major limitations have been identified: (1) single-scale architectures, such as CNNs or standard Transformers, cannot capture thin-layer details less than 0.5 m and regional geological trends larger than 2 m simultaneously; (2) generic imbalance handling techniques, including focal loss alone or basic SMOTE, prove to be insufficient for extreme ratios larger than 50:1; and (3) conventional Transformers lack depth-dependent attention mechanisms incorporating stratigraphic continuity principles. This paper is dedicated to proposing a geological-constrained multi-scale Transformer framework tailored for 1D well-log sequences under extreme imbalance larger than 50:1. The systematic approach addresses the extreme imbalance by deep-feature fusion and advanced class-rebalancing strategies. Accordingly, this framework integrates multi-scale convolutional feature extraction using 1 × 3, 1 × 5, 1 × 7 kernels, hierarchical attention mechanisms with depth-aware position encoding based on Walther’s Law to model long-range dependencies, and adaptive three-stage class-rebalancing through SMOTE–Tomek hybrid resampling, focal loss, and CReST self-training. The experimental validation based on 32,847 logging samples demonstrates significant improvements: overall accuracy reaches 90.3% with minority class F1 scores improving by 20–25% percentage points (argillaceous siltstone 73.5%, calcareous sandstone 68.2%, coal seams 65.8%), and G-mean of 0.804 confirming the balanced recognition. Of note, the framework maintains stable performance even when there is extreme class imbalance at a ratio of up to 100:1 with minority class F1 scores above 64%, representing a two-fold improvement over the state-of-the-art methods, where former Transformer-based approaches degrade below. This paper provides the fundamental technical development for the intelligent transformation of oil and gas exploration, with extensive application prospects. Full article

Neuroblastoma is an embryonal tumour that arises from the malignant transformation of neural crest cells and remains one of the deadliest malignancies in children under five. Neural crest development is regulated by dynamic switches in transcriptional programmes, guided by a variety of growth factors. Due to its developmental origin, neuroblastoma is unique in that these tumours often retain overactivation of growth factor signalling, which can be targeted by receptor tyrosine kinase (RTK) inhibitors. However, mutations in kinases, except for ALK, are extremely rare in neuroblastoma. Furthermore, the high degree of intratumoural heterogeneity often renders RTK inhibition ineffective as a monotherapy. For high-risk tumours, which lack effective treatment options, there remains an unmet need for targeted therapies. This review summarises the roles of growth factor receptors in neural crest and neuroblastoma development in light of recent single-cell studies. We provide a systematic overview of RTK inhibitors that can target growth factor signalling in neuroblastoma and detail their current status in clinical development. We also explore the role of intratumoural heterogeneity in resistance to RTK inhibitors, focusing on the adrenergic-to-mesenchymal transition, which drives a switch in growth factor receptor expression. Finally, we discuss strategies to overcome RTK inhibitor resistance by targeting neuroblastoma cell plasticity, disrupting downstream signalling pathways, or inhibiting escape mechanisms from cell death. This review provides a theoretical basis for developing novel combination therapies incorporating RTK inhibitors. Full article

Objectives: Atypical teratoid/rhabdoid tumors (ATRTs) are rare, malignant central nervous system (CNS) neoplasms that predominantly affect infants and young children. While ATRT arises throughout the CNS, its extracranial counterpart, malignant rhabdoid tumor, occurs in other organs. A single-institutional cohort is reviewed to map anatomic distribution of pediatric ATRTs and to integrate a literature review to contextualize ATRT histogenesis from anatomical and embryological perspectives. Methods: A retrospective review was conducted on a cohort of 50 pediatric patients with ATRT treated over 20 years. Demographic, surgical, and neuroimaging data were correlated to define tumor location, extent, and compartmental involvement. A focused literature review synthesized molecular subclassifications and proposed cells of origin/cytogenesis. Results: Of the 50 ATRTs, 18 (36%) were infratentorial, 15 (30%) supratentorial, 11 (22%) in the pineal region, and 6 (12%) in the spinal compartment. Among infratentorial tumors, 10 were centered in the fourth ventricle, with or without extension into the cerebellopontine angle (CPA) cistern; the remainder arose in the CPA. Among ATRTs of the cerebral hemispheres, 3 showed bi-hemispheric involvement crossing the falx cerebri. ATRTs of the pineal region predominantly originated from the superior medullary velum. These topographic data were corelated with embryological and molecular information available in the literature. Conclusions: ATRTs arise across diverse neuroanatomical compartments—including intraparenchymal, intraventricular, extra-axial, and extradural sites—underscoring biological heterogeneity. Inactivation of SMARCB1 is the defining molecular event and principal oncogenic driver, although the upstream mechanisms precipitating these alterations remain incompletely resolved. Molecular subgroups—ATRT-TYR, ATRT-SHH, and ATRT-MYC—display distinct age distributions and anatomic predilections, implicating developmental context in tumor initiation. The characteristic cellular admixture of rhabdoid cells with mesenchymal and/or epithelial differentiation, together with intra- and extra-axial and occasional extradural presentations, supports a model in which at least a subset of ATRTs may originate from neural crest-derived lineages, despite little or no neural crest contribution to brain parenchyma development. Neural plate border progenitors with bipotent features represent a plausible intraparenchymal cell of origin. Definitive resolution of these origins and the mechanisms of SMARCB1 disruption will require integrated approaches. Further investigations are warranted to clarify these mechanisms. Full article

Children with Hutchinson–Gilford progeria syndrome (HGPS) are born without height and weight abnormalities, and postnatal development is delayed from two months of age. The pathophysiological manifestations of HGPS can be categorized into the three tissue systems that are primarily affected: bone and cartilage, the smooth muscular layer of the vasculature, and the dermis layer. To understand the biology of the syndrome’s complications resulting from the inherited dominant mutation of the LMNA gene, HGPS has to be considered in embryogenesis. Since the development of the primarily affected HGPS tissues involves a simultaneous contribution of mesodermal and neural crest cells, we hypothesized that the stochastic and heterogeneous coexistence of mesoderm and neural crest cells might be crucial for the onset and manifestation of HGPS. In addition, the expression of Lamin A and/or progerin during embryonic development tends to accumulate in the cell nucleus, causing the syndrome manifestation. Then, how and why are infants with the LMNA gene mutation born without severe deviations? Migration is a distinguishing property of mesoderm and neural crest cells, so that they are continuously subjected to mechanical stimuli throughout development and require normal lamina function. However, the viscoelastic property and the mechanosensor capability to respond to mechanical stress of the HGPS cell nucleus are disturbed. Despite the presence of progerin in development, we assume that high levels of Lamin B1 in cells determine the delayed onset of HGPS after birth. We also hypothesized that progerin toxicity could be managed and prevented, potentially allowing for rescue by the presence of Lamin B1. Full article

Rolling element bearing fault diagnosis (BFD) is fundamental to Predictive Maintenance (PdM) strategies for rotating machinery, as early anomaly detection prevents catastrophic failures, reduces unplanned downtime, and optimizes operational costs. This study introduces an interpretable Deep Learning (DL) framework that rigorously compares the performance of an Artificial Neural Network–Multilayer Perceptron (ANN-MLP), a one-dimensional Convolutional Neural Network (1D-CNN), and a ResNet-1D architecture for classifying seven bearing health states using a compact vector of 15 statistical features extracted from vibration signals. Both baseline models (ANN-MLP and 1D-CNN) failed to detect the critical Abrasive Particles fault (F1 = 0.0000). In contrast, the ResNet-1D architecture achieved statistically superior diagnostic performance, successfully resolving the most challenging class with a perfect F1-score of 1.0000 and an overall macro F1-score of 0.9913. This superiority was confirmed by a paired t-test on 100 bootstrap samples, establishing a highly significant difference in performance against the 1D-CNN ($t=592.702$, $p=0.00000$). To boost transparency and trust, the SHapley Additive exPlanations (SHAP) method was applied to interpret the ResNet-1D’s decisions. The SHAP analysis revealed that the Crest Factor from Sensor 1 (Crest_1) exerts the strongest influence on the critical Abrasive Particles fault predictions, physically validating the model’s intelligence against established domain knowledge of impulsive wear events. These findings support transparent, highly reliable, and evidence-based decision-making in industrial PdM applications within Industry 4.0 environments. Full article

Accurate cooling load prediction is essential for energy-efficient HVAC system operation. However, the stochastic and nonlinear nature of load data challenges conventional neural networks, causing prediction delays and errors. To address this, a novel hybrid model is developed. The approach first applies a two-stage decomposition (CEEMDAN with K-means and VMD) to process complex cooling load data. Then, a CNN-BiLSTM network optimized by the Crested Porcupine Optimizer and integrated with an attention mechanism is constructed for prediction. Experimental results demonstrate the model’s high performance, achieving a 96.75% prediction accuracy with a MAPE of 3.25% and an R² of 0.9929. The proposed model shows strong robustness and generalization, providing a reliable reference for intelligent building energy management. Full article

Cancer cell plasticity drives metastasis and therapy resistance through dynamic transitions between epithelial, mesenchymal, and neural crest stem-like (NCSC) states; however, a unifying mechanism that stabilizes these transitions remains undefined. To address this gap, we introduce a N-cadherin (CDH2)-centered redox–adhesion–exosome (RAX) hub that links oxidative signaling, adhesion dynamics, and exosome-mediated immune communication into a closed-loop framework. Within this network, reactive oxygen species (ROS) pulses license epithelial–mesenchymal transition (EMT), AXL–FAK/Src signaling consolidates mesenchymal adhesion, and selective exosomal cargoes—including miR-21, miR-200, miR-210, and PD-L1—propagate plasticity and immune evasion. Lipid peroxidation acts as a central checkpoint connecting ROS metabolism to PUFA membrane remodeling and ferroptosis vulnerability, buffered by NRF2–GPX4 and FSP1/DHODH axes, thereby converting transient oxidative pulses into persistent malignant states. Mechanistically, the RAX hub synthesizes findings from EMT/CSC biology, ferroptosis defenses, and exosome research into a self-reinforcing system that sustains tumor heterogeneity and stress resilience. Evidence from single-cell and spatial transcriptomics, intravital ROS imaging, and exosome cargo-selector studies supports the feasibility of this model. We further outline validation strategies employing HyPer–EMT–CDH2 tri-reporters, CRISPR perturbation of YBX1/ALIX cargo selectors, and spatial multi-omics in EMT-high tumors. Clinically, tumors enriched in EMT/NCSC programs—such as melanoma, neuroblastoma, small-cell lung cancer, pancreatic ductal adenocarcinoma, and triple-negative breast cancer (TNBC)—represent RAX-dependent contexts. These insights highlight biomarker-guided opportunities to target adhesion switches, ferroptosis defenses, and exosome biogenesis through lipid peroxidation-centered strategies using liquid-biopsy panels (exosomal CDH2, miR-200, miR-210) combined with organoid and xenograft models. By linking lipid peroxidation to ferroptosis defense and oxidative stress adaptation, the RAX hub aligns with the thematic focus of lipid metabolism and redox control in cancer progression. Collectively, the RAX framework may provide a conceptual basis for precision oncology by reframing metastasis and therapy resistance as emergent network properties. Full article

Melanoma cells in the brain may use similar mechanisms for adapting to injury and/or disease (that is, through continued reallocation of energy, matter, and information) as other cell types do to create an environment in which cancer cells can grow and sustain themselves within the confines of the brain. These adaptable mechanisms include the ability to reactivate dormant neural crest-derived migration and communication pathways. Unlike some other types of cancers that invade neural tissue as a simple invasion, melanomas are capable of achieving limited molecular, metabolic, and electrical similarity to the neural circuitry of the brain. Melanomas achieve this limited similarity through both vascular co-optation and mimicking synaptic functions, as well as through their engagement of redox-coupled metabolic pathways and feedback-regulated signal transduction pathways. The result is the creation of a metastable tumor–host system, where the relationship between tumor and host is defined by the interaction of stabilizing and destabilizing forces; forces that define the degree of coherence, vulnerability, and persistence of the tumor–host system. In this review, we integrate molecular, electrophysiological, and anatomical data to develop a single unifying hypothesis for the functional integration of melanoma cells into the neural tissue of the brain. Additionally, we describe how neural crest-based regulatory pathways are reactivated in the adult brain and how tumor–host coherence is developed as a function of the shared thermodynamic and informational constraints placed on both tumor and host. We also describe how our proposed conceptual model allows for the understanding of therapeutic interventions as selective disruptions of the neural, metabolic, and immunological couplings that support metastatic adaptation. Full article

Mucosal melanoma (MM) is a rare, aggressive cancer whose incidence has increased continuously over the years. This subtype of melanoma arises from melanocytes on hairless surfaces, typically in the respiratory tract, gastrointestinal (GI) tract, and urogenital tract. The most common sites of occurrence include the head and neck, the anorectal region, and the vulvovaginal region, while the rare sites of MM are the urinary tract and the upper and lower GI tract, including the esophagus, duodenum and the gallbladder. MM arises in melanocytes of the ectodermal mucosa that originate from neural crest cells and migrate through embryonic mesenchyme to their destination. Although melanocytes are located mainly in the epidermis and dermis, their presence in various extracutaneous sites, such as the eyes, mucosal tissue, and leptomeninges, is known. Although both cutaneous melanoma (CM) and MM differ in their epidemiology, genetic profile, and clinical presentation, their treatment options are similar. In contrast to the higher treatment response of CM, MM is characterized by a lower response rate to available treatment options, resulting in a poorer survival rate. In this review, we provide an overview of the biology of MM and the mechanisms regulating its development, progression and treatment resistance. Full article

Aortic aneurysms are complex, predominantly asymptomatic vascular diseases with distinct incidence patterns depending on anatomical localisation. The incidence of thoracic aortic aneurysms (TAAs) has moderately increased, whereas that of abdominal aortic aneurysms has declined, primarily due to public health measures. Undiagnosed or poorly managed aneurysms are at significant risk of progression to acute aortic syndrome, with high associated mortality. The embryological origins of the aorta may have a substantial impact on its structural, cellular, and functional heterogeneity. Specifically, smooth-muscle cells (SMCs) in the thoracic aorta are derived from cardiac neural crest and mesodermal cells, whereas abdominal aortic SMCs originate from the paraxial and splanchnic mesoderm. To explore these developmental and regional distinctions, we conducted a narrative review based on targeted literature retrieval and expert curation, highlighting how these distinctions might potentially influence susceptibility to aneurysms and their clinical presentation. Histological differences, such as the number of lamellar units and the presence or absence of vasa vasorum, could further explain regional vulnerability. Molecular mechanisms underlying aneurysm formation include inflammation, oxidative stress, extracellular matrix degradation, phenotypic switching, and dysregulated signalling pathways, notably transforming growth factor-beta (TGF-β) and angiotensin II. Genetic mutations significantly contribute to TAAs, with genes involved in the elastin–contractile unit and TGF-β signalling pathways playing pivotal roles. However, the complex interplay between genetic susceptibility and risk factors explains why some patients develop aneurysms while others do not. Clinical management strategies have evolved, emphasising early risk stratification, surveillance, and timely surgical intervention, guided increasingly by genetic profiling and segment-specific molecular understanding. Advances in genomic technologies, biomarker identification, and computational modelling promise to enhance individualised care. Bridging developmental biology, molecular genetics, and clinical practice is crucial for improving outcomes in patients with aortic aneurysms, thereby reinforcing a multidisciplinary approach to patient-centred cardiovascular medicine. Full article

The complex nonlinear interplay between preparation parameters and macroscopic properties poses challenges for predicting the performance of anti-aging rubber asphalt. To address this, two bio-inspired algorithms—Crested Porcupine Optimizer (CPO) and Dung Beetle Optimizer (DBO)—were integrated with a backpropagation (BP) neural network, forming CPO-BP and DBO-BP hybrid models for multi-target prediction. The CPO-BP model demonstrated superior predictive accuracy, significantly outperforming both the standard BP and DBO-BP models, which is attributed to its adaptive global-local optimization mechanism. Shapley additive explanations (SHAP) analysis identified mixing temperature as the most influential factor, with elevated values enhancing rutting resistance but compromising ductility, while moderate temperatures improved aging resistance. Feature interactions indicated synergistic effects between mixing temperature and shear time, and a strong coupling effect between rubber content and temperature on low-temperature performance. Parameter optimization via Non-dominated Sorting Genetic Algorithm II (NSGA-II) further enhanced high–low temperature stability and aging resistance, confirmed by Atomic Force Microscopy (AFM)-based microstructural characterization. The proposed approach provides a robust framework that integrates data-driven prediction and multi-objective optimization for the rational design of high-performance anti-aging rubber asphalt. Full article

The carotid body—a chemoreceptive derivative of the neural crest located at the bifurcation of the carotid artery—has been studied for over 282 years. The history of research into this small but vital organ is full of unexpected turns and offers many valuable lessons. Initially considered part of a unified system of paraganglia performing the endocrine function, the carotid body was later reclassified and recognized as a chemosensory organ. This article highlights the key controversies encountered by past researchers. These contradictions though largely forgotten, remain unresolved. The aim of our article is to propose a unified model of the carotid body that integrates its endocrine and chemosensory structural aspects. As we show, the main problem in studying the carotid body was its isolated investigation, detached from other organs of the sympathoadrenal system. Only a comprehensive analysis of the carotid body with other components of this system has allowed researchers to form a more complete understanding of both the structure and function of these formations. Contrary to the prevailing view of the carotid body as the main peripheral chemoreceptor organ, it may also perform endocrine functions during certain periods of human ontogeny. It is these potential functions that may explain the presence of certain morphological structures in the carotid body, the significance of which has until recently remained a mystery. Full article

Pharyngeal cartilage, derived from neural crest cells (NCCs), undergoes complex morphogenesis driven by signals from the pharyngeal endoderm. However, the molecular mechanisms governing NCC proliferation and differentiation in response to endoderm-derived signals remain poorly understood. Here, we investigate the role of klf5a, a zinc-finger transcription factor expressed in pharyngeal endodermal pouches, in zebrafish pharyngeal cartilage development. Knockdown of klf5a using morpholinos minimally affected cranial NCC specification and migration but significantly impaired their proliferation and differentiation in the pharyngeal region. Notably, klf5a deficiency reduced expression of fgfbp2b, a modulator of FGF signaling, in the pharyngeal endoderm. Co-injection of klf5a mRNA rescued the cartilage defects, but injection of fgfbp2b mRNA alone failed to restore normal cartilage morphogenesis, suggesting that fgfbp2b is not the sole mediator of klf5a’s effects. These findings indicate that klf5a regulates endodermal signaling to direct NCC-derived pharyngeal cartilage formation, likely through multiple downstream targets including fgfbp2b. This study provides insights into the complex molecular network underlying craniofacial development and highlights potential therapeutic targets for craniofacial disorders. Full article

Midline facial clefts are severe craniofacial defects that occur due to an underdeveloped frontonasal process. While genetic studies in mice have identified several genes that are crucial for midfacial development, the interactions and regulatory mechanisms of these genes during development remain unclear. In this study, we conducted a systematic review and database search to curate genes associated with midline facial clefts in mice. We identified a total of 78 relevant genes, which included 69 single-gene mutant mice, nine spontaneous models, and 20 compound mutant mice. We then performed bioinformatic analyses with these genes to identify candidate microRNAs (miRNAs) that may regulate the expression of genes related to midline facial clefts. Furthermore, we experimentally evaluated the four highest-ranking candidates—miR-320-3p, miR-381-3p, miR-27a-3p, and miR-124-3p—in O9-1 cells. Our results indicated that overexpression of any of these miRNAs inhibited cell proliferation through the suppression of genes associated with midline facial clefts. Thus, our results suggest that miR-320-3p, miR-381-3p, miR-27a-3p, and miR-124-3p are involved in the cause of midline facial anomalies. Full article