Search Results (3,331)

Understory-cultivated Panax ginseng possesses high pharmacological and economic value; however, its visual quality grading predominantly relies on subjective manual assessment, constraining industrial scalability. To address challenges including fine-grained morphological variations, boundary ambiguity, and complex natural backgrounds, this study proposes Ginseng-YOLO, a lightweight and deployment-friendly object detection model for automated ginseng grade classification. The model is built on the YOLOv11n (You Only Look Once11n) framework and integrates three complementary components: (1) C2-LWA, a cross-stage local window attention module that enhances discrimination of key visual features, such as primary root contours and fibrous textures; (2) ADown, a non-parametric downsampling mechanism that substitutes convolution operations with parallel pooling, markedly reducing computational complexity; and (3) Slide Loss, a piecewise IoU-weighted loss function designed to emphasize learning from samples with ambiguous or irregular boundaries. Experimental results on a curated multi-grade ginseng dataset indicate that Ginseng-YOLO achieves a Precision of 84.9%, a Recall of 83.9%, and an mAP@50 of 88.7%, outperforming YOLOv11n and other state-of-the-art variants. The model maintains a compact footprint, with 2.0 M parameters, 5.3 GFLOPs, and 4.6 MB model size, supporting real-time deployment on edge devices. Ablation studies further confirm the synergistic contributions of the proposed modules in enhancing feature representation, architectural efficiency, and training robustness. Successful deployment on the NVIDIA Jetson Nano demonstrates practical real-time inference capability under limited computational resources. This work provides a scalable approach for intelligent grading of forest-grown ginseng and offers methodological insights for the design of lightweight models in medicinal plants and agricultural applications. Full article

Accurate and non-destructive assessment of fruit firmness is critical for evaluating quality and ripeness, particularly in postharvest handling and supply chain management. This study presents the development of an image-based vibration analysis system for evaluating the firmness of kiwifruit using computer vision and machine learning. In the proposed setup, 120 kiwifruits were subjected to controlled excitation in the frequency range of 200–300 Hz using a vibration motor. A digital camera captured surface displacement over time (for 20 s), enabling the extraction of key dynamic features, namely, the damping coefficient (damping is a measure of a material’s ability to dissipate energy) and natural frequency (the first peak in the frequency spectrum), through image processing techniques. Results showed that firmer fruits exhibited higher natural frequencies and lower damping, while softer, more ripened fruits showed the opposite trend. These vibration-based features were then used as inputs to a feed-forward backpropagation neural network to predict fruit firmness. The neural network consisted of an input layer with two neurons (damping coefficient and natural frequency), a hidden layer with ten neurons, and an output layer representing firmness. The model demonstrated strong predictive performance, with a correlation coefficient (R²) of 0.9951 and a root mean square error (RMSE) of 0.0185, confirming its high accuracy. This study confirms the feasibility of using vibration-induced image data combined with machine learning for non-destructive firmness evaluation. The proposed method provides a reliable and efficient alternative to traditional firmness testing techniques and offers potential for real-time implementation in automated grading and quality control systems for kiwi and other fruit types. Full article

Introduction and Aims: Androgen deprivation therapy (ADT) with systemic anti-cancer treatment (SACT) ± palliative radiotherapy (pRT) is the current standard of care for Oligo-metastatic hormone-sensitive prostate cancer (o-mHSPC). Cytoreductive radical prostatectomy (cRP) has gained interest in this group of patients, with potential benefits including reduced tumour burden and a lower risk of local events from disease progression. In this review, we compare both survival outcomes and local event rates between cRP and upfront ADT ± SACT. Methods: All randomised trials and observational studies comparing cRP with standard treatment (ST), which we defined as ADT ± SACT for o-mHSPC, were included in the review. The study protocol was registered in PROSPERO (CRD42024516586), and the review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The databases searched included Embase, Medline, Cochrane Library, PubMed, and Web of Science. A risk of bias assessment was performed for the included studies as recommended by the Cochrane Handbook of Systematic Reviews and Interventions. The primary outcome measures were Overall Survival (OS), Cancer-Specific Survival (CSS), Progression-free Survival (PFS), Castrate-resistant Prostate Cancer-free Survival (CRPC-FS), and local complication rates. The secondary outcome measures were complication rates and functional outcomes post-cRP. Results: A total of 5130 studies were identified for this review (5119 by database searching and 11 through manual searching). Eight studies were included in the review, comprising 611 patients. cRP was identified to have superior OS (HR: 0.56 (95% CI: 0.34–0.92), I² = 0%, p = 0.02 (very low certainty)) and CSS (HR: 0.27 (95% CI: 0.15–0.47), I² = 0%, p < 0.0001 (very low certainty)). The PFS (HR: 0.67 (95% CI: 0.34–1.33), I² = 58%, p = 0.25 (very low certainty)) and CRPC-FS (HR: 0.67 (95% CI: 0.32–1.43), I² = 57%, p = 0.30 (very low certainty)) were similar between the two groups. The rates of local events were significantly lower in patients undergoing cRP (RR 0.27 (95% CI: 0.13–0.59), I² = 17%, p = 0.001 (low certainty)). The rates of Clavien–Dindo (CD) grade 3 or higher complications ranged from 0% to 13.1%. Additionally, the reported continence rates ranged from 81.5% to 91.3%. The review is limited by the lack of a uniform definition for o-mHSPC and the predominance of low-quality, heterogeneous studies. Despite mitigation strategies, the overall certainty of evidence remains very low per GRADE assessment. Conclusion: cRP significantly reduces local event rates compared with ST and offers comparable PFS and CFPC-FS, with superior OS and CSS in the cRP arm compared to the ST arm in patients with o-mHSPC. However, there is a paucity of high-quality literature on this subject. Ongoing randomised controlled trials may soon clarify the role of cRP in the context of o-mHSPC concerning survival benefits. Full article

As contemporary society and the global economy become increasingly dependent on satellite-based systems, the need for reliable and resilient positioning, navigation, and timing (PNT) services has never been more critical. This study investigates the impact of the geomagnetic storm that occurred in May 2024 on the performance of global navigation satellite system (GNSS) low-cost permanent stations. The research evaluates the influence of ionospheric disturbances on both positioning performance and raw GNSS observations. Two days were analyzed: 8 May 2024 (DOY 129), representing quiet ionospheric conditions, and 11 May 2024 (DOY 132), coinciding with the peak of the geomagnetic storm. Precise Point Positioning (PPP) and static relative positioning techniques were applied to data from a low-cost GNSS station (DYVA), supported by comparative analysis using a nearby geodetic-grade station (TRDS00NOR). The results showed that while RMS positioning errors remained relatively stable over 24 h, the maximum errors increased significantly during the storm, with the 3D positioning error nearly doubling on DOY 132. Short-term analysis revealed even larger disturbances, particularly in the vertical component, which reached up to 3.39 m. Relative positioning analysis confirmed the vulnerability of single-frequency (L1) solutions to ionospheric disturbances, whereas dual-frequency (L1+L2) configurations substantially mitigated errors, highlighting the effectiveness of ionosphere-free combinations during storm events. In the second phase, raw GNSS observation quality was assessed using detrended GPS L1 carrier-phase residuals and signal strength metrics. The analysis revealed increased phase instability and signal degradation on DOY 132, with visible cycle slips occurring between epochs 19 and 21. Furthermore, the average signal-to-noise ratio (SNR) decreased by approximately 13% for satellites in the northwest sky sector, and a 5% rise in total cycle slips was recorded compared with the quiet day. These indicators confirm the elevated measurement noise and signal disruption associated with geomagnetic activity. These findings provide a quantitative assessment of low-cost GNSS receiver performance under geomagnetic storm conditions. This study emphasizes their utility for densifying GNSS infrastructure, particularly in regions lacking access to geodetic-grade equipment, while also outlining the challenges posed by space weather. Full article

Background/Objectives: Recurrent meningiomas remain difficult to manage due to the absence of effective systemic therapies and comparatively high treatment failure rates, particularly in high-grade tumors. Stereotactic radiosurgery (SRS) offers a minimally-invasive and precise option, particularly for tumors in surgically complex locations. However, the risks associated with re-irradiation, and recent changes in the WHO classification of CNS tumors highlight the need for more personalized and strategic treatment approaches. This systematic review evaluates the safety, efficacy, and clinical considerations for use of SRS for recurrent meningiomas. Methods: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature search was conducted using the PubMed, Scopus, and Web of Science databases for studies reporting outcomes of SRS in recurrent, pathologically confirmed intracranial meningiomas. Studies were excluded if they were commentaries, reviews, case reports with fewer than three cases, or had inaccessible full text. The quality and risk of bias of the included studies were assessed using the modified Newcastle-Ottawa Scale. Data on patient and tumor characteristics, SRS treatment parameters, clinical outcomes, adverse effects, and statistical analysis results were extracted. Results: Sixteen studies were included. For WHO Grade I tumors, 3- to 5-year progression-free survival (PFS) ranged from 85% to 100%. Grade II meningiomas demonstrated more variable outcomes, with 3-year PFS ranging from 23% to 100%. Grade III tumors had consistently poorer outcomes, with reported 1-year and 2-year PFS rates as low as 0% and 46%, respectively. SRS performed after surgery alone was associated with superior outcomes, with local control rates of 79% to 100% and 5-year PFS ranging from 40.4% to 91%. In contrast, tumors previously treated with radiotherapy, with or without surgery, showed substantially poorer outcomes, with 3- to 5-year PFS ranging from 26% to 41% and local control rates as low as 31%. Among patients with prior radiotherapy, outcomes were particularly poor in Grade II and III recurrent tumors. Toxicity rates ranged from 3.7% to 37%, and were generally higher for patients with prior radiation. Predictors of worse PFS included prior radiation, older age, and Grade III histology. Conclusions: SRS may represent a reasonable salvage option for carefully selected patients with recurrent meningioma, particularly following surgery alone. Outcomes were notably worse in high-grade recurrent meningiomas following prior radiotherapy, emphasizing the prognostic significance of both histological grade and treatment history. Notably, the lack of molecular and genetic data in most existing studies represents a key limitation in the current literature. Future prospective studies incorporating molecular profiling may improve risk stratification and support more personalized treatment strategies. Full article

Focusing on the characteristic tea resource Zijuan tea, this study addresses the difficulty of grading on production lines and the complexity of quality evaluation. On the basis of the fusion of near-infrared (NIR) spectroscopy and visual features, a novel method is proposed for classifying different tenderness levels and quantitatively assessing key anthocyanin components in Zijuan tea fresh leaves. First, NIR spectra and visual feature data were collected, and anthocyanin components were quantitatively analyzed using UHPLC-Q-Exactive/MS. Then, four preprocessing techniques and three wavelength selection methods were applied to both individual and fused datasets. Tenderness classification models were developed using Particle Swarm Optimization–Support Vector Machine (PSO-SVM), Random Forest (RF), and Convolutional Neural Networks (CNNs). Additionally, prediction models for key anthocyanin content were established using linear Partial Least Squares Regression (PLSR), nonlinear Support Vector Regression (SVR) and RF. The results revealed significant differences in NIR spectral characteristics across different tenderness levels. Model combinations such as TEX + Medfilt + RF and NIR + Medfilt + CNN achieved 100% accuracy in both training and testing sets, demonstrating robust classification performance. The optimal models for predicting key anthocyanin contents also exhibited excellent predictive accuracy, enabling the rapid and nondestructive detection of six major anthocyanin components. This study provides a reliable and efficient method for intelligent tenderness classification and the rapid, nondestructive detection of key anthocyanin compounds in Zijuan tea, holding promising potential for quality control and raw material grading in the specialty tea industry. Full article

Brain tumors elicit complex neuropsychiatric disturbances that frequently occur prior to radiological detection and hinder differentiation from major psychiatric disorders. These syndromes stem from tumor-dependent metabolic reprogramming, neuroimmune activation, neurotransmitter dysregulation, and large-scale circuit disruption. Dinucleotide hypermethylation (e.g., IDH-mutant gliomas), through the accumulation of 2-hydroxyglutarate (2-HG), execute broad DNA and histone hypermethylation, hypermethylating serotonergic and glutamatergic pathways, and contributing to a treatment-resistant cognitive-affective syndrome. High-grade gliomas promote glutamate excitotoxicity via system Xc⁻ transporter upregulation that contributes to cognitive and affective instability. Cytokine cascades induced by tumors (e.g., IL-6, TNF-α, IFN-γ) lead to the breakdown of the blood–brain barrier (BBB), which is thought to amplify neuroinflammatory processes similar to those seen in schizophrenia spectrum disorders and autoimmune encephalopathies. Frontal gliomas present with apathy and disinhibition, and temporal tumors lead to hallucinations, emotional lability, and episodic memory dysfunction. Tumor-associated neuropsychiatric dysfunction, despite increasing recognition, is underdiagnosed and commonly misdiagnosed. This paper seeks to consolidate the mechanistic understanding of these syndromes, drawing on perspectives from neuroimaging, molecular oncology, neuroimmunology, and computational psychiatry. Novel approaches, including lesion-network mapping, exosomal biomarkers or AI-based predictive modeling, have projected early detection and precision-targeted interventions. In the context of the limitations of conventional psychotropic treatments, mechanistically informed therapies, including neuromodulation, neuroimmune-based interventions, and metabolic reprogramming, are essential to improving psychiatric and oncological outcomes. Paraneoplastic neuropsychiatric syndromes are not due to a secondary effect, rather, they are manifestations integral to the biology of a tumor, so they require a new paradigm in both diagnosis and treatment. And defining their molecular and circuit-level underpinnings will propel the next frontier of precision psychiatry in neuro-oncology, cementing the understanding that psychiatric dysfunction is a core influencer of survival, resilience, and quality of life. Full article

Background and Objectives: Human papillomavirus (HPV) is the most prevalent sexually transmitted infection worldwide and, beyond its oncogenic potential, may impair reproductive health in both sexes. This review examines HPV’s effects on male and female fertility, obstetric outcomes, vertical transmission, and fertility-sparing management in oncology. Materials and Methods: A systematic search of PubMed, Embase, and Scopus was conducted using terms related to HPV and reproduction. Additional search terms included those related to therapeutic vaccines, antivirals, and genotype prevalence. English-language human studies reporting clinical reproductive outcomes were included. Thirty-seven studies met the inclusion criteria. Two reviewers independently screened and assessed study quality using a simplified GRADE framework. Results: In men, seminal HPV infection correlates with reduced progressive motility (SMD ≈ −0.85), abnormal morphology, and increased DNA fragmentation. In women, high-risk HPV doubles the odds of infertility (OR ≈ 2.3) and is associated with endometrial involvement. High first-trimester viral load predicts vertical transmission (aOR 6.4), which is also increased by vaginal delivery (RR 1.8) and is linked to PROM (OR 1.8) and preterm birth (OR 1.8). Modeling suggests that nine-valent vaccination plus 5-year HPV-based screening could reduce CIN2+ by up to 80% and excisional treatments by >75%. Fertility-sparing surgery in early cervical cancer yields a <4% recurrence and up to 68% live birth rates. Conclusions: This review uniquely synthesizes reproductive and oncologic impacts of HPV and emphasizes risk stratification, multidisciplinary prevention, and fertility preservation. Integration of HPV DNA quantification, personalized care, and vaccine-based strategies offers a path toward optimized outcomes in both sexes. Full article

Soil fertility is the essential attribute of soil quality. Large-scale coal mining has led to the continuous deterioration of the fragile ecosystems in arid and semi-arid mining areas. As one of the key indicators for land ecological restoration in these coal mining regions, rapidly and accurately monitoring topsoil fertility and its spatial variation information holds significant importance for ecological restoration evaluation. This study takes Wuhai City in the Inner Mongolia Autonomous Region of China as a case study. It establishes and evaluates various soil indicator inversion models using multi-temporal Landsat8 OLI multispectral imagery and measured soil sample nutrient content data. The research constructs a comprehensive evaluation method for surface soil fertility based on multispectral remote sensing monitoring and achieves spatiotemporal variation analysis of soil fertility characteristics. The results show that: (1) The 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum Vector version)-SVM (Support Vector Machine) prediction model for surface soil indicators based on Landsat8 OLI imagery achieved prediction accuracy with R² values above 0.85 for all six soil nutrient contents in the study area, thereby establishing for the first time a rapid assessment method for comprehensive topsoil fertility using multispectral remote sensing monitoring. (2) Long-term spatiotemporal evaluation of soil indicators was achieved: From 2015 to 2025, the spatial distribution of soil indicators showed certain variability, with soil organic matter, total phosphorus, available phosphorus, and available potassium contents demonstrating varying degrees of increase within different ranges, though the increases were generally modest. (3) Long-term spatiotemporal evaluation of comprehensive soil fertility was accomplished: Over the 10 years, Grade IV remained the dominant soil fertility level in the study area, accounting for about 32% of the total area. While the overall soil fertility level showed an increasing trend, the differences in soil fertility levels decreased, indicating a trend toward homogenization. Full article

Optic pathway glioma (OPG) is a rare pediatric low-grade glioma, frequently associated with neurofibromatosis type 1 (NF–1), that presents unique therapeutic challenges due to its anatomical location and its potential to impair vision, endocrine function, and developmental trajectories. Current clinical management prioritizes a multidisciplinary, patient-specific approach aimed at tumor control while preserving long-term quality of life. Strategies vary based on clinical presentation, ranging from observation in asymptomatic cases to chemotherapy for progressive or symptomatic tumors. Surgical and radiation options are limited due to potential risks and complications. In recent years, advances in molecular characterization have guided the development of targeted therapies, particularly MEK inhibitors, which demonstrate encouraging efficacy and reduced toxicity profiles. In parallel, investigational therapies including immunotherapy and precision medicine-based approaches are under clinical evaluation. This review provides a synthesis of current standard practices, emerging targeted treatments, and ongoing clinical trials, drawing on relevant literature and expert consensus to inform clinicians and families about available therapeutic options. Literature discussed in this review was identified through a non-systematic search of published articles, clinical trial registries, and authoritative guidelines, with selection based on relevance, clinical significance, and contribution to understanding current and emerging management strategies for OPG. Full article

Type 2 diabetes (T2D) is a complex metabolic disease characterized by chronic hyperglycemia due to insulin resistance and inadequate insulin secretion. Beyond the classically implicated organs, emerging evidence highlights the gut as a central player in T2D pathophysiology through its interactions with metabolic organs. The gut hosts trillions of microbes and enteroendocrine cells that influence inflammation, energy homeostasis, and hormone regulation. Disruptions in gut homeostasis (dysbiosis and increased permeability) have been linked to obesity, insulin resistance, and β-cell dysfunction, suggesting multifaceted “Gut-X axes” contribute to T2D development. We aimed to comprehensively review the evidence for gut-mediated crosstalk with the pancreas, endocrine system, liver, and kidneys in T2D. Key molecular mechanisms (incretins, bile acids, short-chain fatty acids, endotoxins, etc.) were examined to construct an integrated model of how gut-derived signals modulate metabolic and inflammatory pathways across organs. We also discuss clinical implications of targeting Gut-X axes and identify knowledge gaps and future research directions. A literature search (2015–2025) was conducted in PubMed, Scopus, and Web of Science, following PRISMA guidelines (Preferred Reporting Items for Systematic Reviews). Over 150 high-impact publications (original research and review articles from Nature, Cell, Gut, Diabetologia, Lancet Diabetes & Endocrinology, etc.) were screened. Data on gut microbiota, enteroendocrine hormones, inflammatory mediators, and organ-specific outcomes in T2D were extracted. The GRADE framework was used informally to prioritize high-quality evidence (e.g., human trials and meta-analyses) in formulating conclusions. T2D involves perturbations in multiple Gut-X axes. This review first outlines gut homeostasis and T2D pathogenesis, then dissects each axis: (1) Gut–Pancreas Axis: how incretin hormones (GLP-1 and GIP) and microbial metabolites affect insulin/glucagon secretion and β-cell health; (2) Gut–Endocrine Axis: enteroendocrine signals (e.g., PYY and ghrelin) and neural pathways that link the gut with appetite regulation, adipose tissue, and systemic metabolism; (3) Gut–Liver Axis: the role of microbiota-modified bile acids (FXR/TGR5 pathways) and bacterial endotoxins in non-alcoholic fatty liver disease (NAFLD) and hepatic insulin resistance; (4) Gut–Kidney Axis: how gut-derived toxins and nutrient handling intersect with diabetic kidney disease and how incretin-based and SGLT2 inhibitor therapies leverage gut–kidney communication. Shared mechanisms (microbial SCFAs improving insulin sensitivity, LPS driving inflammation via TLR4, and aryl hydrocarbon receptor ligands modulating immunity) are synthesized into a unified model. An integrated understanding of Gut-X axes reveals new opportunities for treating and preventing T2D. Modulating the gut microbiome and its metabolites (through diet, pharmaceuticals, or microbiota therapies) can improve glycemic control and ameliorate complications by simultaneously influencing pancreatic islet function, hepatic metabolism, and systemic inflammation. However, translating these insights into clinical practice requires addressing gaps with robust human studies. This review provides a state-of-the-art synthesis for researchers and clinicians, underlining the gut as a nexus for multi-organ metabolic regulation in T2D and a fertile target for next-generation therapies. Full article

The development of a new salt–alkaline-tolerant hybrid japonica rice is crucial for enhancing japonica rice supply and ensuring national food security. Utilizing molecular marker-assisted selection (MAS) technology combining Kompetitive Allele-Specific PCR (KASP) markers and a gene breeding chip, the salt-tolerant gene SKC1 was introgressed into a rice genotype Fan 14. This led to the development of Shenyanhui 1, a new high-quality, strongly heterotic, and salt-tolerant japonica restorer line. Subsequently, the high-quality, salt-tolerant japonica three-line hybrid rice variety Shenyanyou 1 was developed by crossing the BT-type japonica cytoplasmic male sterile (CMS) line Shen 21A with the restorer line Shenyanhui 1. Shenyanyou 1 carries the major salt tolerance gene SKC1, exhibiting excellent salt tolerance with seedling stage salt tolerance reaching level 5. Under precise salt tolerance evaluation throughout its growth cycle, Shenyanyou 1 achieved a yield of 3640.5 kg/hm², representing an extremely significant increase of 20.7% over the control variety Yandao 21. Shenyanyou 1 exhibits superior grain quality, meeting the Grade 3 high-quality rice standards issued by the Ministry of Agriculture. Shenyanyou 1 has good comprehensive resistance, aggregating rice blast resistance genes such as Pi2, Pita, Pizt and LHCB5, bacterial blight resistance genes Xa26/Xa3, stripe blast resistance gene STV11, semi-dwarf gene Sdt97, nitrogen-efficient utilization gene NRT1.1B, the light repair activity enhancement gene qUVR-10, the cold resistance gene qLTG3-1, and the iron tolerance gene OsFRO1. It has good resistance to biotic and abiotic stresses. This paper details the breeding process, key agronomic traits, salt tolerance, yield performance, and grain quality characteristics of Shenyanyou 1. Full article

Background/Objectives: Since ChatGPT was released in 2022, many Large Language Models (LLM) have been developed, showing potential to expand the field of orthopaedic surgery. This is the first systematic review looking at the current state of research of LLMs in orthopaedic surgery. The aim of this study is to identify which LLMs are researched, assess their functionalities, and evaluate their quality of results. Methods: The systematic review was conducted using PubMed, Embase, and Cochrane Library databases in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A total of 60 studies were included in the final review, all of which included ChatGPT versions 3.0 or 4.0. There were five studies that included Bard and one article each for Perplexity AI and Bing. Most studies assessed orthopaedic assessment questions (23 studies) and their ability to correctly answer free ended questions (31 studies). Outcome measures used to assess the accuracy of LLMs in most of the included studies were the percentage of correct answers on multiple-choice questions or expert-graded consensus to open-ended responses. The accuracy of ChatGPT 4.0 in orthopaedic assessment questions ranged from 47.2 to 73.6% without images, and 35.7–65.85% with images. The accuracy of ChatGPT 3.5 was 29.4–55.8% without images and 22.4–46.34% with images. The accuracy of Bard ranged from 49.8 to 58%. Orthopaedic residents consistently scored better than LLMs in the range of 74.2–75.3%. Conclusions: ChatGPT 4 showed significant improvement over ChatGPT 3.5 in answering orthopaedic assessment questions. When comparing performances of orthopaedic residents to LLMs, orthopaedic residents scored higher overall. There remains significant opportunity for development of LLM performance on orthopaedic assessments as well as image-based analysis and clinical documentation. Full article

Maximal safe surgical resection remains a critical component of glioblastoma (GBM) management, improving both survival and quality of life. However, complete tumor removal is hindered by the infiltrative nature of GBM and its proximity to eloquent brain regions. Fluorescence-guided surgery (FGS) has emerged as a valuable tool to enhance intraoperative tumor visualization and optimize resection outcomes. Currently used fluorophores such as 5-aminolevulinic acid (5-ALA), fluorescein sodium (FS), and indocyanine green (ICG) have distinct advantages but are limited by suboptimal specificity, shallow tissue penetration, and technical constraints. 5-ALA and SF often yield unreliable signals in low-grade tumors or infiltrative regions and also pose challenges such as phototoxicity and poor depth resolution. In contrast, near-infrared (NIR) fluorescence imaging represents a promising next-generation approach, providing superior tissue penetration, reduced autofluorescence, and real-time delineation of tumor margins. This review explores the mechanisms, clinical applications, and limitations of currently approved FGS agents and highlights future directions in image-guided neurosurgery. Full article

The nutritional value of lipids depends not only on their fatty acid composition but also on their stereospecific positioning on the glycerol backbone. This study investigated the fatty acid composition and sn-2 positional distribution of triacylglycerols (TAG), as well as the composition of major phospholipids in golden pompano (Trachinotus ovatus) juveniles (initial weight: 10 g) fed five diets including graded levels of dietary n-3 highly unsaturated fatty acids (HUFA; 0.64–2.10%) for 56 days. With increasing dietary n-3 HUFA levels, the proportions of eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), and total n-3 HUFA in muscle TAG, phosphatidylcholine (PC), and phosphatidylethanolamine (PE) significantly increased. Phospholipids, especially PC and PE, were preferentially enriched with n-3 HUFA, and the sn-2 positions of TAG showed a significantly increased deposition of DHA and reduced n-6/n-3 ratios. RNA-Seq analysis was performed on muscle tissues of T. ovatus subjected to different dietary n-3 HUFA levels to further investigate the molecular mechanisms of lipid compositional and structural changes. A total of 126,792 unigenes were obtained, of which 47.78% were successfully annotated. KEGG pathway enrichment analysis implicated the glycerophospholipid, glycerolipid, and sphingolipid metabolism pathways in lipid composition and distribution regulation, identifying gpat4, agpat3, agpat8, lpeat1, and lpgat1 as potential regulators. These findings offer insights into lipid remodeling in marine fish and support strategies to enhance aquaculture product quality. Full article