Search Results (1,644)

Addressing the technical demands for the rapid, precise detection of earthquake-triggered landslides in loess tablelands, this study proposes and validates an innovative methodology integrating enhanced deep learning architectures with large-tile processing strategies, featuring two core advances: (1) a critical enhancement of YOLOv8’s shallow layers via a higher-resolution P2 detection head to boost small-target capture capabilities, and (2) the development of a large-tile segmentation–tile mosaicking workflow to overcome the technical bottlenecks in large-scale high-resolution image processing, ensuring both timeliness and accuracy in loess landslide detection. This study utilized 20 km² of high-precision UAV imagery acquired after the 2023 Gansu Jishishan Ms 6.2 earthquake as foundational data, applying our methodology to achieve the rapid detection and precise segmentation of landslides in the study area. Validation was conducted through a comparative analysis of high-accuracy 3D models and field investigations. (1) The model achieved simultaneous convergence of all four loss functions within a 500-epoch progressive training strategy, with mAP50(M) = 0.747 and mAP50-95(M) = 0.46, thus validating the superior detection and segmentation capabilities for the Jishishan earthquake-triggered loess landslides. (2) The enhanced algorithm detected 417 landslides with 94.1% recognition accuracy. Landslide areas ranged from 7 × 10⁻⁴ km² to 0.217 km² (aggregate area: 1.3 km²), indicating small-scale landslide dominance. (3) Morphological characterization and the spatial distribution analysis revealed near-vertical scarps, diverse morphological configurations, and high spatial density clustering in loess tableland landslides. Full article

Elevated extracellular potassium (K⁺) in the tumor microenvironment (TME) of breast and other cancers is increasingly recognized as a critical factor influencing tumor progression and immune suppression. Current methods for noninvasive mapping of the potassium distribution in tumors are limited. Here, we employed photoacoustic chemical imaging (PACI) with a solvatochromic dye-based, potassium-sensitive nanoprobe (SDKNP) to quantitatively visualize extracellular potassium levels in an orthotopic metaplastic breast cancer mouse model, Ccn6-KO. Tumors of three distinct sizes (5 mm, 10 mm, and 20 mm) were imaged using multi-wavelength photoacoustic imaging at five laser wavelengths (560, 576, 584, 605, and 625 nm). Potassium concentration maps derived from spectral unmixing of the photoacoustic images at the five laser wavelengths revealed significantly increased potassium levels in larger tumors, confirmed independently by inductively coupled plasma mass spectrometry (ICP-MS). The PACI results matched ICP-MS measurements, validating PACI as a robust, noninvasive imaging modality for potassium mapping in tumors in vivo. This work establishes PACI as a promising tool for studying the chemical properties of the TME and provides a foundation for future studies evaluating the immunotherapy response through ionic biomarker imaging. Full article

This study proposed an online early lameness detection method for dairy cow health management to overcome the inability of wearable sensor-based methods for online detection and low sensitivity to early lameness. Wearable IMU sensors collected acceleration data in stationary and moving states; a threshold discrimination module using variance of motion-direction acceleration was designed to distinguish states within 2 s, enabling rapid data screening. For moving-state windowed data, the InceptionTime network was modified with YOLOConv1D and SeparableConv1D modules plus Dropout, which significantly reduced model parameters and helped mitigate overfitting risk, enhancing generalization on the test set. Typical gait features were fused with deep features automatically learned by the network, enabling accurate discrimination among healthy, mild (early) lameness, and severe lameness. Results showed that the online detection model achieved 80.6% dairy cow health status detection accuracy with 0.8 ms single-decision latency. The recall and F1 score for lameness, including early and severe cases, reached 89.11% and 88.93%, demonstrating potential for early and progressive lameness detection. This study improves lameness detection efficiency and validates the feasibility and practical value of wearable sensor-based gait analysis for dairy cow health management, providing new approaches and technical support for monitoring and early intervention on large-scale farms. Full article

Adipose stem cells (ASCs) are a subset of mesenchymal stem cells with validated immunomodulatory and regenerative capabilities that make them attractive tools for treating neurodegenerative disorders, such as multiple sclerosis (MS). Several studies conducted on experimental autoimmune encephalomyelitis (EAE), the animal model of MS, have clearly shown a therapeutic effect of ASCs. However, controversial data on their efficacy were obtained from I- and II-phase clinical trials in MS patients, highlighting standardization issues and limited data on long-term safety. In this context, ASC-derived extracellular vesicles from (ASC-EVs) represent a safer, more reproducible alternative for EAE and MS treatment. Moreover, their physical characteristics lend themselves to a non-invasive, efficient, and easy handling of intranasal delivery. Using an in vitro setting, we first verified ASC-EVs’ ability to cross the human nasal epithelium under an inflammatory milieu. Magnetic resonance corroborated these data in vivo in intranasally treated MOG35-55-induced EAE mice, showing a preferential accumulation of ASC-EVs in brain-inflamed lesions compared to a stochastic distribution in healthy control mice. Moreover, intranasal treatment of ASC-EVs at the EAE onset led to a long-term therapeutic effect using two different experimental protocols. A marked reduction in T cell infiltration, demyelination, axonal damage, and cytokine production were correlated to EAE amelioration in ASC-EV-treated mice compared to control mice, highlighting the immunomodulatory and neuroprotective roles exerted by ASC-EVs during EAE progression. Overall, our study paves the way for promising clinical applications of self-administered ASC-EV intranasal treatment in CNS disorders, including MS. Full article

Oligodendrocyte precursor cells (OPCs) are a distinct and dynamic glial population that retain proliferative and migratory capacities throughout life. While traditionally recognized for differentiating into oligodendrocytes (OLs) and generating myelin to support rapid nerve conduction, OPCs are now increasingly appreciated for their diverse and non-canonical roles in the central nervous system (CNS), including direct interactions with neurons. A notable feature of OPCs is their expression of diverse ion channels that orchestrate essential cellular functions, including proliferation, migration, and differentiation. Given their widespread distribution across the CNS, OPCs are increasingly recognized as active contributors to the development and progression of various neurological disorders. This review aims to present a detailed summary of the physiological and pathological functions of ion channels in OPCs, emphasizing their contribution to CNS dysfunction. We further highlight recent advances suggesting that ion channels in OPCs may serve as promising therapeutic targets across a broad range of disorders, including, but not limited to, multiple sclerosis (MS), spinal cord injury, amyotrophic lateral sclerosis (ALS), psychiatric disorders, Alzheimer’s disease (AD), and neuropathic pain (NP). Finally, we discuss emerging therapeutic strategies targeting OPC ion channel function, offering insights into potential future directions in the treatment of CNS diseases. Full article

The aim of this study was to analyze and compare the external load demands of players from the Spanish women’s national football teams across the U-17, U-20, and senior categories during their respective FIFA World Cup participations. Key kinematic variables were assessed via global positioning systems (GPS), including total distance (TD), high-speed running (HSR; ≥18 km·h⁻¹), sprint distance (≥21 km·h⁻¹), accelerations (>3 m·s⁻²), decelerations (<–3 m·s⁻²), and high metabolic load distance (HMLD) during 3 world cups (U17, U20 and senior). Significant differences were observed between the senior team and both U-20 and U-17 in nearly all variables, with greater magnitude as the intensity of the metrics increased, showing effect sizes ranging from moderate to very large (d = 0.95 to 4.76). Positional analysis by categories showed that senior full backs (FB) and central midfielders (CM) showed higher demands compared to U-20 and U-17. For TD, senior covered more than U-17 (FB: p = 0.001; d = 1.11 | CM: p = 0.023; d = 0.97), with small differences vs. U-20 (d ≤ 0.54). In HSR, both positions outperformed U-17 and U-20 (FB: p ≤ 0.007; d = 0.87–1.15 | CM: p ≤ 0.031; d = 0.71–1.11). In HMLD, both FB and CM displayed very large differences compared to U-17 and U-20 (all p < 0.001; d = 2.54–6.16). These findings underscore the need for progressive development of locomotor capacities from early stages, considering both age category and playing position, to facilitate a more seamless transition to elite-level football. Full article

Huntington’s disease (HD) is characterized by progressive neurodegeneration, but increasing evidence points to multisystemic involvement, including early hepatic steatosis in pediatric HD. Therefore, it is important to consider systemic alterations, particularly in liver lipid metabolism. In this study, we analyzed fatty acid (FA) profiles in two symptomatic HD mouse models: 2-month-old R6/2 mice representing early-onset HD and 22-month-old Hdh^Q150/Q150 (Hdh) mice representing late-onset HD, along with age-matched wild-type (WT) controls. FA composition in liver tissue was assessed by gas chromatography–mass spectrometry (GC–MS). In R6/2 mice, we observed increased levels of total iso-branched chain, monounsaturated, and n-6 polyunsaturated FAs compared to WT. In contrast, only a few FA species showed reduced concentrations in Hdh mice. Overall, our results indicate that R6/2 mice exhibit more pronounced alterations in hepatic FA profiles than Hdh mice, suggesting that early-onset HD may be associated with more severe peripheral metabolic dysregulation. Full article

Real-time quality monitoring using molten pool images is a critical focus in researching high-quality, intelligent automated welding. To address interference problems in molten pool images under complex welding scenarios (e.g., reflected laser spots from spatter misclassified as porosity defects) and the limited interpretability of deep learning models, this paper proposes a multi-granularity spatiotemporal representation learning algorithm based on the hybrid enhancement of handcrafted and deep learning features. A MobileNetV2 backbone network integrated with a Temporal Shift Module (TSM) is designed to progressively capture the short-term dynamic features of the molten pool and integrate temporal information across both low-level and high-level features. A multi-granularity attention-based feature aggregation module is developed to select key interference-free frames using cross-frame attention, generate multi-granularity features via grouped pooling, and apply the Convolutional Block Attention Module (CBAM) at each granularity level. Finally, these multi-granularity spatiotemporal features are adaptively fused. Meanwhile, an independent branch utilizes the Histogram of Oriented Gradient (HOG) and Scale-Invariant Feature Transform (SIFT) features to extract long-term spatial structural information from historical edge images, enhancing the model’s interpretability. The proposed method achieves an accuracy of 99.187% on a self-constructed dataset. Additionally, it attains a real-time inference speed of 20.983 ms per sample on a hardware platform equipped with an Intel i9-12900H CPU and an RTX 3060 GPU, thus effectively balancing accuracy, speed, and interpretability. Full article

Breast cancer (BC) is a neoplasm characterized by high heterogeneity and is influenced by intrinsic molecular subtypes and clinical stage, aspects that remain underexplored in the Colombian population. This study aimed to characterize metabolic alterations associated with subtypes and disease progression in a group of newly diagnosed, treatment-naive Colombian women using an untargeted metabolomics approach. To improve metabolite coverage, samples were analyzed using LC-QTOF-MS and GC-QTOF-MS, along with amino acid profiling. The Luminal B subtype exhibited elevated levels of long-chain acylcarnitines and higher free fatty acid concentrations than the other subtypes. It also presented elevated levels of carbohydrates and essential glycolytic intermediates, suggesting that this subtype may adopt a hybrid metabolic phenotype characterized by increased glycolytic flux as well as enhanced fatty acid catabolism. Tumor, Node, and Metastasis (TNM) staging analysis revealed progressive metabolic reprogramming of BC. In advanced stages, a sustained increase in phosphatidylcholines and a decrease in lysophosphatidylcholines were observed, reflecting lipid alterations associated with key roles in tumor progression. In early stages (I-II), plasma metabolites with high discriminatory power were identified, such as glutamic acid, ribose, and glycerol, which are associated with dysfunctions in energy and carbohydrate metabolism. These results highlight metabolomics as a promising tool for the early diagnosis, clinical follow-up, and molecular characterization of BC. Full article

Background/Objectives: Pediatric acquired demyelinating syndromes (ADSs) encompass a heterogeneous group of disorders, including multiple sclerosis (MS), MOG antibody-associated disease (MOGAD), and neuromyelitis optica spectrum disorder (NMOSD), with distinct clinical trajectories and prognoses. While analyzed collectively at baseline to reflect real-world diagnostic uncertainty, outcome predictors were also examined according to final diagnosis. Identifying early predictors is crucial for optimizing long-term outcomes. Methods: We retrospectively analyzed 30 pediatric patients (mean onset age: 11.3 years) with ADSs. Clinical, radiological, CSF, antibody, and neurophysiological data were collected and analyzed alongside treatment strategies. Outcomes—EDSS scores, neuroradiological changes, and clinical status—were evaluated over a 3-year period. Results: Final diagnoses included MOGAD (36.6%), MS (33.3%), NMOSD (6.6%), ADEM (10%), and other ADSs (13.3%). At onset, ≥3 brain lesions were present in 76.7% of patients. Disease-modifying therapies (DMTs) were used in 37% and acute immunotherapy in 90%. EDSS progression was significantly associated with DMT use at multiple timepoints, with additional predictors including MRI lesion type, CSF findings, antibody status, and evoked potentials. At 3 years, neurocognitive function predicted clinical outcome. Conclusions: Early immunotherapy and baseline instrumental findings are key predictors of outcome in pediatric ADSs. MOGAD showed a more favorable course, while MS and NMOSD were associated with greater long-term disability. A comprehensive, early diagnostic approach is essential for improving prognosis. Full article

Background/Objectives: Gut dysbiosis has been implicated in multiple sclerosis (MS), but microbial signatures remain inconsistent across studies. Machine learning (ML) algorithms based on global microbiome data integration can reveal key disease-associated microbial biomarkers and new insights into MS pathogenesis. This study aimed to investigate gut microbial signatures associated with MS and to evaluate the potential of ML for diagnostic applications. Methods: Fecal samples from 29 relapsing–remitting MS patients during exacerbation and 27 healthy controls were analyzed using 16S rRNA gene sequencing. Differential abundance analysis was performed, and data were integrated with 29 published studies. Four ML models were developed to distinguish MS-associated microbiome profiles. Results: MS patients exhibited reduced levels of Eubacteriales (p = 0.037), Lachnospirales (p = 0.021), Oscillospiraceae (p = 0.013), Lachnospiraceae (p = 0.012), Parasutterella (p = 0.018), Faecalibacterium (p = 0.004), and higher abundance of Lachnospiraceae UCG-008 (p = 0.045) compared to healthy controls. The Light Gradient Boosting Machine classifier demonstrated the highest performance (accuracy: 0.88, AUC-ROC: 0.95) in distinguishing MS microbiome profiles from healthy controls. Conclusions: This study highlights specific microbiome dysbiosis in MS patients and supports the potential of ML for diagnostic applications. Further research is needed to elucidate the mechanistic role of these microbial alterations in MS progression and their therapeutic utility. Full article

Aquilaria sinensis (Lour.) Gilg, the exclusive botanical source of Chinese agarwood, holds significant medicinal value. This study investigated the agarwood-inducing potential of a Fusarium strain obtained through prior isolation work. Through integrated morphological characterization and molecular phylogenetic analysis, the strain was conclusively identified as Fusarium equiseti. GC-MS analysis revealed that fungal inoculation induced the synthesis of characteristic sesquiterpenes and aromatic compounds consistent with natural agarwood profiles. Quantitative determination demonstrated progressive accumulation of agarotetrol, a key quality marker, reaching 0.034%, 0.039%, and 0.038% at 2, 4, and 6 months post-inoculation, respectively—significantly exceeding levels from physical wounding (p < 0.05) and PDA control treatments. Histological examination showed characteristic yellow-brown oleoresin deposits concentrated in the inner phloem, mirroring the anatomical features of wild-type agarwood. Critical quality parameters measured in December-harvested samples included ethanol extractives (17.69%), chromone derivatives 2-[2-(4-methoxyphenyl) ethyl] chromone, and 2-(2-phenylethyl) chromone (2.13%), all meeting or surpassing the specifications outlined in the National Standard for Agarwood Classification (LY/T 3223-2020). These comprehensive findings establish F. equiseti as a promising microbial agent for sustainable agarwood production in A. sinensis plantations. Full article

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the fastest-growing hepatic disorders worldwide. During its natural course, MASLD tends to progress from isolated steatosis of the liver to Metabolic Dysfunction-Associated Alcoholic Steatohepatitis (MASH), advanced fibrosis, and finally cirrhosis, with the risk of developing hepatocellular carcinoma (HCC). Although frequently related to overweight or obesity and other components of the metabolic syndrome (MS), MASLD can also be present in individuals without such risk factors. The mechanisms leading to MASLD are incompletely elucidated and may involve many proinflammatory and pro-fibrotic pathways, disrupted biliary acid homeostasis, and gut microbiota dysbiosis. Aldosterone and its interaction with the mineralocorticoid receptor (MR) are thought to participate in the pathogenesis of MASLD through the modulation of inflammation and fibrosis. Remarkably, blockade of the MR in experimental models was shown to improve MASH and fibrosis through mechanisms that need further characterization. So far, however, few clinical studies have explored the effect of MR blockade in the management of MASH and associated fibrosis. This review is intended to summarize the recent animal and human data concerning the interaction between MR pathways and MASLD. Full article

Daucus is a large genus of the Apiaceae family, comprising around forty-five accepted species, that has a worldwide distribution. Species of this genus have been reported to have several traditional medicinal uses, and some of them are also largely used as food and spices. Daucus nebrodensis Strobl. is an endemic species of Sicily growing in the montane environments of the Madonie and the Nebrodi Mountains. In this work, the essential oil of D. nebrodensis (DnEO), collected wild near Messina (Italy), was chemically and biologically investigated. The hydrodistilled essential oil (yield 0.15%), obtained from fresh aerial parts, was evaluated by GC-MS, and It was particularly rich in monoterpene hydrocarbons, with sabinene (33.6%), α-pinene (17.2%), γ-terpinene (9.8%), and α-terpinene (7.6%) as the main metabolites. DnEO, and its main constituents, have been tested to evaluate their biological properties. Given the current problem of antibiotic resistance, it is of great interest to identify alternative molecules that could counteract the its progression. Therefore, DnEO was tested against Gram-negative species, such as E. coli DH5α and P. aeruginosa PAOI, and Gram-positive species, such as S. aureus ATCC6538P, B. subtilis AZ54, and M. smegmatis MC²155, showing notable antibacterial activity. The MIC for Bacillus subtilis, the most sensitive strain, was 18 mg/mL, while the MIC for Pseudomonas aeruginosa, the least sensitive strain, was 30 mg/mL. Moreover, interesting antibiofilm activity was observed against Mycobacterium smegmatis with a 55% inhibition. Its ability to form biofilms contributes to its persistence and resistance in clinical settings. These findings highlight the potential of D. nebrodensis EO as a source of bioactive compounds with promising antimicrobial and antibiofilm properties. Full article

The combined use of serum and CSF biomarkers for prognostic stratification in multiple sclerosis (MS) remains underexplored. This multicenter observational study investigated associations between serum neurofilament light chain (sNfL), glial fibrillary acidic protein (sGFAP), and CSF lipid-specific IgM oligoclonal bands (LS-OCMB) with different forms of disability worsening, such as relapse-associated worsening (RAW), active progression independent of relapse activity (aPIRA), and non-active PIRA (naPIRA). A total of 535 patients with MS were included, all sampled within one year of disease onset. Biomarkers were quantified using single-molecule array and immunoblotting techniques, and CSF cell subsets were analyzed by flow cytometry. High sNfL z-scores and LS-OCMB positivity were independently associated with increased risk of RAW and aPIRA, collectively termed inflammatory-associated worsening (IAW), while elevated sGFAP levels predicted naPIRA. Patients with both high sNfL and LS-OCMB positivity had the highest risk of IAW. Among LS-OCMB–positive patients, higher regulatory T cell percentages were associated with lower sNfL levels, suggesting a protective role. Conversely, in LS-OCMB–negative patients, sNfL levels correlated with CSF C3 concentrations. These findings support the complementary role of sNfL, sGFAP, and LS-OCMB in identifying distinct mechanisms of disease worsening and may inform early personalized management strategies in MS. Full article