Search Results (330)

Cellular transplantation therapies have been extensively used in experimental spinal cord injury research. However, there is no consensus as to what the most effective cellular controls for the therapeutic cell of interest are. For this reason, we examined whether dead cells obtained through prolonged heat treatment can act as an appropriate cellular control for intravenously injected Sca-1+ mesenchymal precursor cells (MPCs) in C5 unilateral contusion cervical spinal cord injury. This was tested in single intravenous MPC injection alone or intravenous MPC plus intraspinal neural stem cell (NSC) combinatory transplantation studies. MPCs were isolated from the compact bone of FVB mice, while NSCs were isolated from the subventricular zone of luciferase–GFP transgenic FVB mice. Dead MPCs were obtained by heating at 72 °C for at least 12 h. In the MPC-ikofrt\Rftuen45only transplant study, injured mice received an injection of 1 × 10⁶ dead or live MPCs D1 post-injury. Mice were then sacrificed at 8 weeks post-injury. In this study, intravenous injections of dead MPCs showed no statistical difference in injured paw usage compared to live MPCs, but behavior was improved compared to the media-vehicle-only control at D7 and D21. In the combinatory MPC plus NSC transplant study, injured mice received an intravenous injection of 1 × 10⁶ dead or live MPCs D1 post-injury followed by intraspinal injection of 100,000 NSCs at D3 or D7 post-injury. Another two cohorts of mice received only NSCs at D3 or D7 post-injury. Mice were then sacrificed at 6 weeks post-injury. In this study, there was no functional difference in any of the groups in the dual injection study. Morphologically, mice receiving IV injection of dead MPCs had a smaller lesion size compared to the vehicular control, but the lesion size was larger than that of the lesion size in mice receiving live MPC injection. Dead cells elicited functional and anatomical benefits for the spinal-cord-injured mice. In summary, dead cells obtained through prolonged heat treatment proved to be inconsistent and not optimal for use as cellular controls for cell transplantation studies in spinal cord injury but provide positive evidence for non-transplantation-based cell therapies. Full article

The dye-sensitized solar cell (DSSC) is a promising candidate, offering an attractive substitute for conventional silicon-based photovoltaic technologies. The performance advantages of the DSSC have led to a surge in research activity reflected in the number of publications over the years. To deliver data-driven analysis of DSSC performance, machine learning models have been applied. As a first step, a literature-based database has been developed and after the data preprocesses, Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), xgboost (XGB), and Artificial Neural Network (ANN) algorithms were applied with stratified train-test splits. The performance of the models has been assessed via metrics, and the model interpretability relied on SHAP analysis. Based on the employed metrics and the confusion matrix, DT, RF, and KNN are the most accurate models for predicting DSSC efficiency on the developed dataset. Furthermore, it was revealed that synthesis temperature and the thickness of thin film were identified as the dominant drivers, followed by precursor and dye. Mid-tier contributors were morphological structure, electrolyte concentrations, and the absorption maximum. The results suggest that in optimizing the manufacturing process, targeted tuning of the synthesis temperature, the thickness of thin film, the precursor, and the dye are likely to improve the performance of the device. Therefore, experimental effort should concentrate on these factors. Full article

Background: Multiple sclerosis is a multifactorial neurodegenerative disease characterized by autoimmune and inflammatory processes. Despite advancements in disease-modifying therapies, multiple sclerosis remains challenging due to its complex pathophysiology and variable clinical presentation. Current therapies focus on managing inflammation and promoting immunosuppression but do not achieve complete symptom regression or enhance remyelination. Emerging therapies, such as Peroxisome Proliferator-Activated Receptor gamma (PPARγ) agonists and Bruton tyrosine kinase (BTK) inhibitors, show promise in modulating inflammation and targeting immune cells. Innovative approaches like human fetal neural precursor cells (hfPNCs) and mesenchymal stem cell transplantation are being explored to reduce neural inflammation and improve neuroprotection. Early diagnosis and intervention are crucial for managing multiple sclerosis effectively and preventing progression to severe forms and permanent disability. Therapeutic education for individuals with multiple sclerosis and their caregivers is essential, emphasizing the need for clear, reliable information to support disease management and improve quality of life. Objectives: This review provides an up-to-date overview of multiple sclerosis pathophysiology, current treatments, and emerging therapies, aiming to enhance the knowledge base of healthcare professionals and researchers, facilitating informed decision-making and contributing to ongoing research efforts. Full article

Human induced pluripotent stem cells (hiPSCs) hold great potential for patient-specific therapies. Transplantation of hiPSC-derived neural progenitor cells (NPCs) is a promising reparative strategy for spinal cord injury (SCI), but clinical translation requires efficient differentiation into desired neural lineages and purification before transplantation. Here, differentiated hiPSCs—reprogrammed from human skin fibroblasts using Sendai virus-mediated expression of OCT4, SOX2, KLF4, and C-MYC—into neural rosettes expressing SOX1 and PAX6, followed by neuronal precursors (β-tubulin III⁺/NESTIN⁺) and glial precursors (GFAP+/NESTIN+). Both neuronal and glial precursors expressed the A2B5 surface antigen. A2B5+ NPCs, purified by fluorescence-activated cell sorting (FACS), proliferated in vitro with mitogens, and differentiated into mature neurons and astrocytes under lineage-specific conditions. Then, NOD-SCID mice received a T9 contusion injury followed by transplantation of A2B5+ NPCs, human fibroblasts, or control medium at 8 days post-injury. At two months, grafted NPCs showed robust survival, progressive neuronal maturation (β-tubulin III⁺→doublecortin⁺→NeuN⁺), and astrocytic differentiation (GFAP+), particularly in spared white matter. Transplantation significantly increased spared white matter volume and improved hindlimb locomotor recovery, with no teratoma formation observed. These results demonstrate that hiPSC-derived, FACS-purified A2B5+ NPCs can survive, differentiate into neurons and astrocytes, and enhance functional recovery after SCI. This approach offers a safe and effective candidate cell source for treating SCI and potentially other neurological disorders. Full article

The vertical profile of PM_2.5 is important for understanding its secondary formation, transport, and deposition at high altitudes; it also provides important data support for studying the causes and sources of PM_2.5 near the ground. Based on machine learning methods, this study fully utilized simultaneous Multi-Axis Differential Optical Absorption Spectroscopy measurements of multiple air pollutants in the atmosphere and employed the measured vertical profiles of aerosol extinction—as well as the vertical profiles of precursors such as NO₂ and SO₂—to evaluate the vertical distribution of PM_2.5 concentration. Three machine learning models (eXtreme Gradient Boosting, Random Forest, and back-propagation neural network) were evaluated using Multi-Axis Differential Optical Absorption Spectroscopy instruments in four typical cities in China: Beijing, Lanzhou, Guangzhou, and Hefei. According to the comparison between estimated PM_2.5 and in situ measurements on the ground surface in the four cities, the eXtreme Gradient Boosting model has the best estimation performance, with the Pearson correlation coefficient reaching 0.91. In addition, the in situ instrument mounted on the meteorological observation tower in Beijing was used to validate the estimated PM_2.5 profile, and the Pearson correlation coefficient at each height was greater than 0.7. The average PM_2.5 vertical profiles in the four typical cities all show an exponential pattern. In Beijing and Guangzhou, PM_2.5 can diffuse to high altitudes between 500 and 1000 m; in Lanzhou, it can diffuse to around 1500 m, while it is primarily distributed between the near surface and 500 m in Hefei. Based on the vertical distribution of PM_2.5 mass concentration in Beijing, a high-altitude PM_2.5 pollutant transport event was identified from January 19th to 21st, 2021, which was not detected by ground-based in situ instruments. During this process, PM_2.5 was transported from the 200 to 1500 m altitude level and then sank to the near surface, causing the concentration on the ground surface to continuously increase. The sinking process contributes to approximately 7% of the ground surface PM_2.5 every hour. Full article

Obesity is an epidemic that currently impacts many nations. The persistence of this disease is shaped by both genetic and epigenetic factors that extend beyond calorie balance. Research in the past year has revealed that epigenetic and cellular memory within adipose tissue can predispose individuals to weight regain after initial fat loss, as shown by studies indicating persistent transcriptional and chromatin changes even after fat mass reduction. Independent studies also demonstrate long-lasting metabolic shifts, such as those triggered by glucose-dependent insulinotropic polypeptide receptor (GIPR)-induced thermogenesis and sarcolipin (SLN) stabilization that also support a form of “metabolic memory” that is associated with sustained weight loss. At the neural level, rare variants in synaptic genes like BSN (Bassoon presynaptic cytomatrix protein), a presynaptic scaffold protein, and APBA1 (amyloid beta precursor protein binding family A member 1), a neuronal adaptor involved in vesicular trafficking, disrupt communication in feeding circuits, elevating obesity risk and illustrating how synaptic integrity influences food intake regulation. Similarly, the spatial compartmentalization of metabolic signaling within neuronal cilia is emerging as crucial, with cilia-localized receptors G protein-coupled receptor 75 (GPR75) and G protein-coupled receptor 45 (GPR45) exerting opposing effects on energy balance and satiety. Meanwhile, genome-wide association studies (GWAS) have advanced through larger, more diverse cohorts and better integration of environmental and biological data. These studies have identified novel obesity-related loci and demonstrated the value of polygenic risk scores (PRS) in predicting treatment responses. For example, genetic variants in GLP-1R (glucagon-like peptide-1 receptor) and GIPR (glucose-dependent insulinotropic polypeptide receptor) may modulate the effectiveness of incretin-based therapies, while PRS for satiation can help match individuals to the most appropriate anti-obesity medications. This review focuses on studies in the last two years that highlight how advances in obesity genetics are driving a shift toward more personalized and mechanism-based treatment strategies. Full article

Tissue engineering has the potential to overcome the limitations of using autografts in nerve gap repair, using cellular biomaterials to bridge the gap and support neuronal regeneration. Various types of therapeutic cells could be considered for use in aligned collagen-based engineered neural tissue (EngNT), including Schwann cells and their precursors, which can be derived from human induced pluripotent stem cells (hiPSCs). Using Schwann cell precursors may have practical advantages over mature Schwann cells as they expand readily in vitro and involve a shorter differentiation period. However, the performance of each cell type needs to be tested in EngNT. By adapting established protocols, hiPSCs were differentiated into Schwann cell precursors and Schwann cells, with distinctive molecular profiles confirmed using immunocytochemistry and RT-qPCR. For the first time, both cell types were incorporated into EngNT using gel aspiration–ejection, a technique used to align and simultaneously stabilise the cellular hydrogels. Both types of cellular constructs supported and guided aligned neurite outgrowth from adult rat dorsal root ganglion neurons in vitro. Initial experiments in a rat model of nerve gap injury demonstrated the extent to which the engrafted cells survived after 2 weeks and indicated that both types of hiPSC-derived cells supported the infiltration of host neurons, Schwann cells and endothelial cells. In summary, we show that human Schwann cell precursors promote infiltrating endogenous axons in a model of peripheral nerve injury to a greater degree than their terminally differentiated Schwann cell counterparts. Full article

Whilst typically benign, a subset of meningiomas displays aggressive and recurrent behavior. There is a paucity of reliable treatment options for this subset of patients and a relative lack of consensus on how to best manage these patients. This clinical challenge reflects underlying molecular complexity, driven by NF2, TRAF7, and CDKN2A/B mutations alongside pervasive epigenetic dysregulation. High-throughput molecular profiling studies have proposed biologically distinct meningioma subgroups with varying clinical trajectories and therapeutic vulnerabilities. Distinct cell lineages of meningeal precursors are now appreciated to be essential in the establishment of the meninges. The numerous cellular lineages involved in meningeal development, the heterogeneity of meningioma location and (epi)genomic behavior, and the variability in its clinical and radiological manifestations raise the question of what critical insights can be gained by understanding meningeal development during embryogenesis to understand meningioma tumorigenicity. The current paper examines this paradigm by highlighting spatially linked mechanisms of anaplasia and treatment resistance, including the role of neural crest-derived convexity meninges in promoting dedifferentiation via YAP/TAZ signaling and mesoderm-derived skull base regions in maintaining TRAF7-mediated vulnerabilities. We further elucidate the emerging synthetic lethal paradigms, CRISPR-enabled target discovery, and PROTAC-mediated degradation strategies that may transform the therapeutic landscape of clinically challenging meningiomas driven by complex oncogenic circuitry. By bridging embryogenesis, spatial genomics, and molecular targeting, we propose a developmentally informed, lineage-stratified model for advancing precision therapeutics in high-grade and recurrent meningiomas. Full article

Geopolymers are an environmentally sustainable class of low-calcium alkali-activated materials (AAMs), distinct from high-calcium C–A–S–H gel systems. Synthesized from aluminosilicate-rich precursors such as fly ash, metakaolin, slag, waste glass, and coal gasification fly ash (CGFA), geopolymers offer a significantly lower carbon footprint, valorize industrial by-products, and demonstrate superior durability in aggressive environments compared to Ordinary Portland Cement (OPC). Recent advances in thermodynamic modeling and phase chemistry, particularly in CaO–SiO₂–Al₂O₃ systems, are improving precursor selection and mix design optimization, while Artificial Neural Network (ANN) and hybrid ML-thermodynamic approaches show promise for predictive performance assessment. This review critically evaluates geopolymer chemistry and composition, emphasizing precursor reactivity, Si/Al and other molar ratios, activator chemistry, curing regimes, and reaction mechanisms in relation to microstructure and performance. Comparative insights into alkali aluminosilicate (AAS) and aluminosilicate phosphate (ASP) systems, supported by SEM and XRD evidence, are discussed alongside durability challenges, including alkali–silica reaction (ASR) and shrinkage. Emerging applications ranging from advanced pavements and offshore scour protection to slow-release fertilizers and biomedical implants are reviewed within the framework of the United Nations Sustainable Development Goals (SDGs). Identified knowledge gaps include standardization of mix design, LCA-based evaluation of novel precursors, and variability management. Aligning geopolymer technology with circular economy principles, this review consolidates recent progress to guide sustainable construction, waste valorization, and infrastructure resilience. Full article

The evolutionary loss of ednrb2 in specific vertebrate lineages, such as mammals and cypriniform fish, raises fundamental questions about its functional necessity and potential redundancy or synergy with paralogous endothelin receptors in pigment cell development. In teleosts possessing both ednrb1a and ednrb2 (e.g., Nile tilapia), their respective and combined roles in regulating neural crest-derived pigment cell precursors remains unresolved. Using CRISPR/Cas9, we generated single and double ednrb mutants to dissect their functions. We demonstrated that ednrb1a and ednrb2 synergistically govern the differentiation and migration of iridophore precursors. While ednrb1a is broadly essential for iridophore development, ednrb2 plays a unique and indispensable role in the colonization of iridophores in the dorsal iris. Double mutants exhibit near-complete iridophore loss; severe depletion of melanophores, xanthophores, and erythrophores; and a striking, fertile, transparent phenotype. Crucially, this iridophore deficiency does not impair systemic guanine synthesis pathways. mRNA rescue experiments confirmed mitfa as a key downstream effector within the Ednrb signaling cascade. This work resolves the synergistic regulation of pigment cell fates by Ednrb receptors and establishes a mechanism for generating transparent ermplasm. Full article

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

The application of artificial intelligence through the brain–computer interface (BCI) is proving to be one of the great advances in neuroscience today. The development of surface electrodes over the cortex and very fine electrodes that can be stereotactically implanted in the brain have moved the science forward to the extent that paralyzed people can play chess and blind people can read letters. However, the introduction of foreign bodies into deeper parts of the central nervous system results in foreign body reaction, scarring, apoptosis, and decreased signaling. Implanted electrodes activate microglia, causing the release of inflammatory factors, the recruitment of systemic inflammatory cells to the site of injury, and ultimately glial scarring and the encapsulation of the electrode. Recordings historically fail between 6 months and 1 year; the longest BCI in use has been 7 years. This article proposes a biomolecular strategy provided by angiogenic cell precursors (ACPs) and nerve cell precursors (NCPs), administered intrathecally. This combination of cells is anticipated to sustain and promote learning across the BCI. Together, through the downstream activation of neurotrophic factors, they may exert a salutary immunomodulatory suppression of inflammation, anti-apoptosis, homeostasis, angiogenesis, differentiation, synaptogenesis, neuritogenesis, and learning-associated plasticity. Full article

Radon anomalies have long been explored as potential geochemical precursors to seismic activity due to their responsiveness to subsurface stress variations. However, before this study, the scientific progression of this research domain had not been systematically examined through a quantitative lens. This study presents a comprehensive bibliometric analysis of 379 articles published between 1977 and 2025 and indexed in Scopus and Web of Science. Utilizing the Bibliometrix R-package and its Biblioshiny interface, the analysis investigates temporal publication trends, leading countries, institutions, international collaboration networks, and thematic evolution. The results reveal a marked increase in research output since 2010, with China, India, and Italy emerging as the most prolific contributors. Thematic mapping indicates a shift from conventional geochemical monitoring toward the integration of artificial intelligence techniques, such as decision trees and neural networks, for anomaly detection and predictive modeling. Notwithstanding this methodological evolution, core research themes remain centered on radon concentration monitoring and the analysis of environmental parameters. Overall, the findings highlight the coexistence of traditional and emerging approaches, emphasizing the importance of standardized methodologies and interdisciplinary collaboration. This bibliometric synthesis provides strategic insights to inform future research and strengthen the role of radon monitoring in seismic early warning systems. Full article

Background: Colorectal cancer (CRC) is a major contributor to cancer mortality on a global scale, with polyps being critical precursors. The accurate classification of colorectal polyps (CRPs) from colonoscopy images is essential for the timely diagnosis and treatment of CRC. Method: This research proposes a novel hybrid model, CRP-ViT, integrating ResNet50 with Vision Transformers (ViTs) to enhance feature extraction and improve classification performance. This study conducted a comprehensive comparison of the CRP-ViT model against traditional convolutional neural networks (CNNs) and emerging quantum neural networks (QNNs). Experiments were conducted for binary classification to predict the presence of polyps and multi-classification to predict specific polyp types (hyperplastic, adenomatous, and serrated). Results: The results demonstrate that CRP_QNN-ViT achieved superior classification performance while maintaining computational efficiency. CRP_QNN-ViT achieved an accuracy of 98.18% for training and 97.73% for validation on binary classification and 98.13% during training and 97.92% for validation on multi-classification tasks. In addition to the key metrics, computational parameters were compared, where CRP_QNN-ViT excelled in computational time. Conclusions: This comparative analysis reveals the potential of integrating quantum computing into medical image analysis and underscores the effectiveness of transformer-based architectures for CRP classification. Full article

Industrial development has increased environmental dioxin concentrations, sparking concern about human health impacts. Examining dioxin neurotoxicity has highlighted associations with cognitive impairment and behavioral abnormality. Dioxins are ligands of the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor; it is speculated that dioxin-induced AHR activation is pivotal for toxic effects. Accurate AHR-expressing cell identification is therefore indispensable for understanding the molecular and cellular mechanisms of dioxin toxicity. Herein, current knowledge regarding AHR expression in the mammalian brain is summarized, and dioxin neurotoxicity mechanisms are discussed. Histological studies show AHR-expressing neurons in multiple brain regions, including the hippocampus and cerebral cortex. Dopaminergic and noradrenergic neurons exhibit AHR expression, suggesting possible roles in the monoaminergic system. AHR overactivation evokes dendritic arborization atrophy, whereas its deficiency increases complexity, implying that AHR-mediated signaling is crucial for neuronal growth and maturation. AHR is also involved in neurogenesis and neuronal precursor migration. Collectively, these findings support the notion that dioxin-induced AHR overactivation in individual neurons disrupts neural circuit structure, ultimately leading to impaired brain function. However, as AHR downstream signaling is intertwined with various molecules and pathways, the precise mechanisms remain unclear. Further studies on the expression, signaling, and roles of AHR are needed to clarify dioxin neurotoxicity. Full article