Search Results (2,535)

Introduction: Pituitary carcinoma (PC) is a rare, aggressive endocrine neoplasm characterized by metastasis and challenging clinical management. The transformation from pituitary adenoma (PA) to PC is poorly understood, and predictors of metastasis remain elusive. This study evaluates the clinical course, surgical outcomes, and molecular characteristics of PC. Methods: We retrospectively reviewed patients with PC treated at the M. D. Anderson Cancer Center between 1993 and 2023. Primary outcomes included metastasis-free survival and overall survival (OS). Clinical features, radiographic findings, surgical strategies and outcomes, immunohistochemical profiles, and MIB-1 were analyzed. Results: The cohort (n = 20) had a median age at PA and PC diagnosis of 33.9 and 43.3 years, respectively. The median metastasis-free interval was 7.4 years. GH- and ACTH-secreting tumors showed shorter times to PC diagnosis, while nonfunctioning PAs had longer metastasis-free survival. PAs with MIB-1 > 10% had shorter survival. Dura was the most common site of metastasis within the CNS, and bone was the most common outside the CNS. Leptomeningeal disease was seen in six patients. PAs became aggressive > five years after initial surgical resection (n = 13) or metastasized early within the first five years (n = 7). Median OS from PA diagnosis was 13.7 years, and 8.6 years from PC diagnosis. A total of 102 neurosurgical procedures were performed, with a median of five per patient; the median was similar in patients surviving longer than five years vs. those whose survival was shorter (5.0 vs. 4.5 procedures, p = 0.661). Most surgical interventions post-PC diagnosis were for optic decompression or metastasectomy. All long-term survivors (at least five years after PC diagnosis) received temozolomide-based therapy, with most also receiving radiotherapy. Conclusions: PC shows a variable clinical course, with some PAs progressing to PC after years, while others transform rapidly. All long-term survivors received temozolomide-based therapy, most in combination with radiotherapy and repeated surgical intervention, suggesting that aggressive multimodal management may be associated with prolonged survival. Future research will focus on identifying reliable predictors of metastasis at different time points in the complex clinical evolution of these tumors. Full article

Background/Objectives: Glioblastoma multiforme (GBM) treatment is limited by tumor hypoxia and poor specificity of therapeutic agents. To address these challenges, we developed brain-targeted liposomes co-encapsulating 5-aminolevulinic acid (5-ALA) and catalase (CAT), termed brain-targeted 5-ALA-CAT liposomes (BACL), which were surface-modified with the Angiopep-2 ligand to enhance blood–brain barrier penetration and achieve multimodal therapy combining targeted delivery and oxygen generation. Methods: BACL was prepared and characterized. Tumor targeting was verified by flow cytometry and in vivo imaging. In vitro antitumor activity was evaluated by wound-healing assay, colony formation assay, live/dead staining, MTT assay, and Western blotting. In vivo efficacy, apoptosis, and safety were assessed in a subcutaneous xenograft model. Transcriptome sequencing and qRT-PCR were employed to identify molecular mechanisms and novel targets. Results: BACL exhibited favorable physicochemical properties (size: 122.4 nm, PDI: 0.189, zeta potential: −12.3 mV) and spherical morphology as observed by TEM, with encapsulation efficiencies of 51.2% for 5-ALA and 43.8% for CAT. Compared with unmodified 5-ALA, BACL increased the cellular uptake efficiency by 1.6-fold in glioma cells while maintaining catalytic stability for sustained oxygen generation. In vitro experiments demonstrated that BACL significantly inhibited glioma cell migration, colony formation, and cell viability, and induced apoptosis. In a subcutaneous xenograft tumor model, BACL-mediated photodynamic therapy (PDT) achieved a tumor growth inhibition rate of 52%, with apoptosis induction via regulation of Bcl-2, Bax, and p53 expression, and no obvious toxicity to major organs was observed. Transcriptomic analysis combined with qRT-PCR validation revealed that BACL activates multiple antitumor signaling pathways, including targeted inhibition of IL-10 and CXCL13 to disrupt cytokine–receptor interactions, as well as coordinated regulation of S100A3 and IGSF-9 expression to suppress glioma progression. Conclusions: These multimodal actions enhanced PDT efficacy while remodeling the tumor microenvironment. Our findings position BACL as a promising therapeutic platform integrating targeted delivery, hypoxia alleviation, and immunomodulation for GBM therapy. Full article

Chronic pain is increasingly understood as a multidimensional condition in which, in a substantial subgroup of patients, a protective symptom can evolve into a persistent maladaptive disorder of the nervous system, while in others it may remain closely tied to ongoing mechanical or structural factors. Central sensitization (CS) represents a key mechanism underlying this transition, characterized by enhanced neural responsiveness and impaired endogenous pain inhibition, leading to a dissociation between pain and tissue pathology. The aim of this narrative review is to critically discuss current evidence on CS as a mechanism-based explanation for persistent pain, using lumbar disk herniation (LDH) as a clinical model of the radiological-clinical mismatch, and to discuss its direct implications for identifying sensitized phenotypes, multimodal assessment, and rehabilitation strategies. A total of 77 sources published between 2006 and 2026 were synthesized. These reviewed sources demonstrate that identification of the sensitized phenotype requires a multimodal assessment approach combining self-report measures, such as the Central Sensitization Inventory (CSI), with psychophysical methods including quantitative sensory testing (QST) and conditioned pain modulation (CPM). Cognitive-emotional factors are also critical, as postoperative kinesiophobia affects approximately 38.3% of LDH patients and is associated with increased pain intensity and reduced self-efficacy. Management strategies reported in these publications focus on mechanism-based interventions, particularly pain neuroscience education (PNE) and graded, time-contingent exercise, which aim to modify pain-related cognitions and restore endogenous inhibitory processes. These approaches may be supported by adjunctive therapies, including dry needling (DN), electro-dry needling (EDN), centrally acting pharmacological agents (e.g., serotonin–norepinephrine reuptake inhibitors [SNRIs] and gabapentinoids), and psychologically informed treatments such as cognitive behavioral therapy (CBT). While surgical decompression may reduce CS-related symptoms, preoperative sensitization does not necessarily predict poorer outcomes, highlighting the interaction between peripheral and central mechanisms. Adopting a sensitization-informed perspective may encourage a broader integration of contemporary pain models alongside traditional structural views in lumbar disc herniation clinical care. Full article

Background and Clinical Significanc: Neuropathic corneal pain is a debilitating condition characterized by ocular pain disproportionate to clinical signs, often resulting from peripheral and central sensitization of the corneal somatosensory pathway. Emerging evidence suggests that chronic involuntary muscle contraction in blepharospasm may lead to irritation of trigeminal afferents and corneal neurogenic inflammation, potentially predisposing patients to neuropathic corneal pain. Given its debilitating nature, early recognition can prevent the progression of neuropathic sequelae. This study examines the potential role of blepharospasm as a predisposing factor contributing to neuropathic corneal pain. Case Presentation: This retrospective case series describes three cases (median age: 50 years) of neuropathic corneal pain in association with blepharospasm and their clinical course following multimodal treatment over a median follow-up period of one year. Ocular surface was evaluated using slit-lamp biomicroscopy, while corneal nerve structure and morphology were assessed with in vivo confocal microscopy. All the three subjects presented with minimal ocular surface staining but disproportionate ocular pain characterized by burning sensation and photophobia. Proparacaine challenge testing was performed to determine the subtype of neuropathic corneal pain. Pain symptoms and quality of life were evaluated using the Ocular Pain Assessment Survey and Ocular Surface Disease Index questionnaires. In vivo confocal microscopy demonstrated characteristic corneal nerve abnormalities including reduced corneal nerve density, increased nerve tortuosity, and the presence of microneuromas. Treatment included oral Pregabalin or Gabapentin, topical lubricants, Cyclosporine 0.05% (1 case), and 20% autologous serum eye drops (1 case). Two of the three cases received four to five injections of botulinum toxin for blepharospasm, whereas one had undergone a single injection prior to review. All patients also received weekly periorbital quantum molecular resonance electrotherapy for two months. Improvements were observed across multiple domains of the Ocular Pain Assessment Survey and Ocular Surface Disease Index evaluation, including ocular pain, photophobia, non-ocular pain, and quality-of-life measures following multimodal treatment. The co-existence of blepharospasm and neuropathic corneal pain observed in our cases supports a possible association between chronic periocular muscle hyperactivity and corneal nociceptor sensitization. Proposed mechanisms include chronic trigeminal nerve irritation, neurogenic inflammation, and sensitization mediated by pro-inflammatory neuropeptides. Multimodal treatment targeting both motor hyperactivity and neuropathic pain pathways appeared to provide symptomatic relief, including the use of quantum molecular resonance electrotherapy, which might modulate pain pathways, block nociceptor neurotransmission, and accelerate corneal nerve regeneration. Given the complexity of the neural pathways responsible for ocular discomfort, further studies are required to elucidate the relationship between neuropathic corneal pain and blepharospasm in larger cohorts, as well as refine existing therapeutic approaches, including evaluating the therapeutic role of electrotherapy. Conclusions: Blepharospasm may represent a potential predisposing factor of neuropathic corneal pain. Early recognition and concurrent treatment of blepharospasm and neuropathic corneal pain can effectively relieve symptoms and improve quality of life. Adopting a multimodal treatment approach is therefore recommended. Full article

Background: Rosacea is a chronic inflammatory dermatosis characterized by vascular dysregulation, immune dysfunction, neurovascular alterations, and microbial involvement. Recent advances in understanding its pathophysiology have led to the development of targeted therapeutic strategies addressing multiple disease mechanisms. This systematic review aimed to evaluate contemporary evidence regarding emerging and established treatment approaches for rosacea. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Scopus, and Web of Science were searched for studies published between 2016 and 2025. Original human studies evaluating therapeutic interventions for rosacea were included. Study selection, data extraction, and risk-of-bias assessment were performed independently by two reviewers. Methodological quality was assessed using Joanna Briggs Institute (JBI) critical appraisal tools appropriate for each study design. Results: Fifteen studies involving 537 patients with rosacea and 77 controls (614 participants in total) met the eligibility criteria. Evaluated interventions included vascular-targeted therapies, topical anti-inflammatory agents, systemic and immunomodulatory treatments, and microbiome-oriented approaches. Oxymetazoline, pulsed-dye laser, platelet-rich plasma, ivermectin, azelaic acid, dapsone, sulfur preparations, and metronidazole demonstrated clinical benefits in reducing erythema, inflammatory lesions, or overall disease severity. Emerging therapies, including tofacitinib and oral ivermectin, showed promising results in refractory disease. Microbiome-related interventions, particularly Demodex-targeted therapies and Helicobacter pylori eradication, were also associated with clinical improvement. Risk-of-bias assessment identified two studies with low risk of bias, twelve with moderate risk of bias, and one study with high risk of bias. Conclusions: Current evidence supports a multimodal and mechanism-based approach to rosacea management, integrating vascular, inflammatory, immunological, and microbiological targets. However, the available evidence remains limited by small sample sizes, heterogeneous methodologies, short follow-up periods, and a predominance of non-randomized study designs. Large, well-designed randomized controlled trials are needed to establish optimal evidence-based treatment strategies and define the long-term efficacy and safety of emerging therapies. Full article

Background: Dedicated artificial intelligence (AI) systems for fracture detection already exist, yet general-purpose multimodal models are increasingly accessible to clinicians despite not being developed or formally validated as medical devices. Their behavior in focused orthopedic imaging tasks remains insufficiently characterized. Purpose: To characterize how two accessible general-purpose multimodal models interpret AP pelvis radiographs with hip fractures, focusing on context dependence, overconfidence, and complementary error patterns within a surgically confirmed positive-only cohort. This was a behavioral characterization study of a fracture-positive cohort, not a diagnostic accuracy evaluation. Methods: In April 2026, we retrospectively studied 214 surgically confirmed hip fractures on AP pelvis radiographs using two general-purpose multimodal models under six prompting conditions. In runs A–D, the models were explicitly told that a hip fracture was present and were asked to classify it; in runs E–F, they were not told whether a hip fracture was present. Each image was rerun de novo in a separate chat session through vendor APIs using a fixed base prompt and no image preprocessing. We recorded hip-fracture detection, correct laterality, coarse fracture pattern, intracapsular displacement, AO/OTA grading, subtrochanteric identification, and self-reported confidence. Because the cohort contained hip fractures only, we report fracture-detection rates and classification performance within a positive-only cohort rather than full diagnostic-accuracy metrics. Results: Using the more conservative endpoint of hip-fracture detection with correct laterality, GPT-5.4 was correct in 79.0% and 86.4% of cases in runs E and F, whereas Gemini was correct in 80.4% and 93.5%, respectively. When outputs from both models were combined, this endpoint reached 89.7% in run E and 96.7% in run F, indicating complementary rather than redundant error patterns. Incorrect laterality cues markedly degraded performance, from 90.7% to 66.4% in GPT-5.4 and from 97.7% to 57.0% in Gemini. Performance remained limited for treatment-relevant subtyping, particularly AO/OTA grading and subtrochanteric identification. Both models frequently remained highly confident when wrong, and self-reported confidence did not reliably distinguish correct from incorrect outputs. Conclusions: Accessible general-purpose multimodal models showed partial capability for coarse hip-fracture interpretation, but they remained context-sensitive, unreliable for treatment-relevant subtyping, and highly confident even when incorrect. Their complementary error patterns are hypothesis-generating rather than evidence of clinical readiness. On the basis of these findings, we do not support unvalidated or uncontrolled clinical use of such models. As access to these tools expands, explicit usage boundaries, minimum performance expectations, repeated local revalidation, and sustained human oversight become increasingly necessary. Full article

The most persistent biomedical challenges of the 21st century are neurodegenerative disorders (NDs), where molecular alterations lead to devastating clinical consequences and progressive neuronal loss. The prevalence of neurodegeneration is continuously rising and becoming the main contributor to chronic disability and mortality. Despite their clinical differences, many conditions share pathogenic processes, including oxidative stress, protein misfolding and aggregation, mitochondrial dysfunction, and neuroinflammation. Instead of functioning independently, these processes cooperate to form a self-reinforcing network that gradually weakens synapses and ultimately leads to neuronal death. This study redefines neurodegeneration as a disorder of system-level failure by emphasizing poor cellular stress integration. In addition to demonstrating how gut microbiome gene networks impact inflammation and amyloid production, new research highlights the relationships between mitochondrial–lysosomal interactions, endoplasmic reticulum stress responses, and transcriptionally driven synaptic vulnerability. A key molecular topic is the interaction and pathogenic convergence of the JAK/STAT, HIF-1α, and Notch signaling pathways. Under ongoing metabolic stress, prolonged stimulation of this triad increases inflammation, hinders the regenerative processes, and maintains pseudo-hypoxic conditions, explaining why single-target treatments have mostly been unsuccessful. This review also explores progress in fluid, digital, and imaging biomarkers that facilitate early diagnosis and patient stratification, and assesses new disease-modifying approaches such as antisense oligonucleotides, immunomodulators, gene therapies, and small-molecular agents. Artificial intelligence is emphasized as an essential tool for integrating multimodal data, drug discovery and predictive modeling. Full article

Congestion is a major driver of symptoms, hospitalization, and adverse outcomes in heart failure (HF), yet its clinical assessment remains challenging. Traditional approaches based on physical examination, biomarkers, and isolated imaging surrogates often fail to capture the complexity of systemic venous congestion and its impact on organ function. In HF, congestion should be interpreted as a multifactorial process resulting from the interaction between intravascular volume burden, venous compliance, cardiac filling pressures, neurohormonal activation, blood volume redistribution, and organ-specific susceptibility. In this context, point-of-care ultrasound has emerged as a promising adjunctive tool for bedside congestion assessment. The Venous Excess Ultrasound (VExUS) score integrates inferior vena cava assessment with Doppler analysis of hepatic, portal, and intrarenal veins, allowing for the evaluation of venous pressure transmission and organ-level congestion. Observational studies suggest that VExUS and related venous Doppler abnormalities correlate with invasive hemodynamic parameters and are associated with acute kidney injury, diuretic response, heart failure hospitalization, and mortality. Serial changes in venous congestion may provide additional information regarding treatment response and clinical trajectory. However, the available evidence remains heterogeneous across acute HF, ambulatory HF, cardiorenal syndrome, and critical care populations, and randomized trials evaluating VExUS-guided management are lacking. Therefore, VExUS should be interpreted as a complementary tool within a multimodal assessment that includes echocardiography, lung ultrasound, biomarkers, renal function, urine output, physical examination, and response to therapy. By integrating fluid burden with venous pressure transmission and organ perfusion, multimodal ultrasound may support more individualized congestion assessment and risk stratification in HF. Full article

Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases—including Parkinson’s disease, atypical parkinsonism, cerebellar ataxias, stroke, multiple sclerosis, neuropathies, neuromuscular disorders, and functional gait syndromes—gait disturbances are among the most disabling clinical features, contributing to falls, loss of independence, institutionalization, and premature mortality. Traditional bedside observation remains indispensable, but it lacks the sensitivity and reproducibility needed to capture subtle, episodic, or prodromal abnormalities. Over the past decade, advances in wearable sensors, marker-based and markerless motion capture, pressure-sensitive walkways, force plates, artificial intelligence, and machine learning have positioned digital mobility outcomes as promising, ecologically valid biomarkers of neurological function. These measures can support differential diagnosis, provide prognostic information on falls and survival, and serve as sensitive endpoints in therapeutic trials. They may also detect early abnormalities, such as increased stride-to-stride variability or prolonged double-support time, before overt clinical deterioration becomes evident. Clinical applications are increasingly evident across disorders, including distinguishing Parkinson’s disease from atypical parkinsonism, quantifying treatment response in normal-pressure hydrocephalus, tracking progression in ataxia and multiple sclerosis, predicting functional decline in motor neuron disease, and guiding rehabilitation after stroke. Integration with neuroimaging, electrophysiology, and molecular biomarkers is beginning to reveal the circuits underlying variability, instability, and freezing, positioning gait as a systems-level marker of neural integrity. Nevertheless, methodological heterogeneity, limited disease-specific validation, insufficient longitudinal data, and lack of consensus on clinically meaningful parameters continue to constrain translation. Cognitive, affective, and environmental influences also remain insufficiently represented in digital frameworks, while equity, accessibility, algorithmic bias, and privacy require careful ethical governance. Reconceptualizing gait as a “sixth vital sign” reframes mobility as a multidimensional biomarker of neural and systemic health. With harmonized protocols, robust validation, multimodal integration, and appropriate ethical frameworks, gait analysis could become a cornerstone of precision neurology. Full article

Bladder cancer is a common malignancy with high recurrence rates and significant morbidity, necessitating accurate diagnostic and prognostic tools. Although cystoscopy and transurethral resection of bladder tumor (TURBT) remain reference standards, these approaches are invasive and limited by sampling errors and understaging. Consequently, there is growing interest in non-invasive biomarkers, including urine-based assays, blood-based markers, and imaging-derived parameters. Among these biomarkers, multiparametric magnetic resonance imaging (mpMRI), particularly with the Vesical Imaging Reporting and Data System (VI-RADS), has emerged as a robust non-invasive imaging biomarker for local staging and risk stratification. Recent evidence suggests that mpMRI plays a role in predicting treatment response and recurrence, particularly in the context of neoadjuvant therapy. This review provides a comprehensive overview of current non-invasive diagnostic and prognostic biomarkers in bladder cancer, with a particular emphasis on imaging biomarkers. We discuss their clinical utility, limitations, and future integration into multimodal decision-making frameworks. Full article

Background/Objectives: Peri-implant diseases, encompassing peri-implant mucositis and peri-implantitis, affect 43% and 18.8–23% of implant-bearing patients, respectively, representing significant clinical challenges in implant dentistry. While mechanical debridement remains foundational, biologically active materials offer promising adjunctive regenerative strategies. This narrative review synthesises current evidence regarding five biologically active materials: enamel matrix derivative (EMD), platelet-rich fibrin (PRF), fibroblast growth factor-2 (FGF-2), recombinant human platelet-derived growth factor-BB (rhPDGF-BB/GEM 21S^®), and polynucleotide–hyaluronic acid combinations (Regenfast^®). Methods: The relevant literature was identified using electronic databases, including MEDLINE, PubMed, Scopus, and Google Scholar. This review focused on clinical studies and randomised controlled trials with a minimum follow-up of six months investigating biologically active materials in peri-implant disease management. Material mechanisms, clinical efficacy, therapeutic limitations, and evidence quality were systematically evaluated. Attention was directed toward identifying genuine biological distinctions between peri-implant and periodontal disease contexts. Results: EMD demonstrates efficacy exclusively within multimodal surgical protocols, with isolated application yielding limited benefits. rhPDGF-BB shows superior periodontal regenerative capacity; however, dedicated peri-implantitis trials remain absent. FGF-2 exhibits paradoxical osteogenic suppression despite bone fill achievement, limiting peri-implant applicability. PRF and Regenfast^® demonstrate a mechanistically sound rationale yet lack substantive peri-implant disease validation. The critical findings revealed that peri-implant regeneration fundamentally differs from periodontal regeneration: implants lack periodontal ligament anatomy, rendering ligamentogenic differentiation-promoting agents biologically inappropriate. Conclusions: Contemporary biologically active materials demonstrate compelling periodontal efficacy yet remain inadequately validated for peri-implantitis management. This disparity reflects authentic biological distinctions rather than insufficient investigation. Until multicentre randomised controlled trials stratify efficacy across distinct peri-implant disease presentations, practitioners must prioritise evidence-based surgical fundamentals—meticulous decontamination, strategic grafting, and optimised wound healing—integrating biologically active materials judiciously within comprehensive, anatomy-respecting treatment protocols. Full article

Background/Objectives: Early recurrence after curative-intent resection is a major determinant of poor prognosis in hepatocellular carcinoma (HCC). Artificial intelligence (AI)-driven predictive models have emerged to identify patients at high risk of recurrence but remain incompletely synthesized for early recurrence specifically. This review aimed to identify and appraise AI-driven models predicting early recurrence after surgical resection. Methods: PubMed/MEDLINE, Scopus and Web of Science were searched from inception to November 2025. Eligible studies developed and evaluated AI-driven models predicting early recurrence (≤24 months) after curative-intent hepatectomy as first-line treatment for HCC. Risk of bias and applicability were assessed using PROBAST+AI, and findings were synthesized narratively due to methodological heterogeneity. The review was registered in PROSPERO. Results: Thirty-six studies involving 14,716 patients were included. Most studies originated from China (33/36, 91.7%), were single-center (27/36, 75%), and retrospective (35/36, 97.2%). Magnetic resonance imaging (MRI) was the predominant imaging modality (15/36, 41.7%), followed by computed tomography (CT) (11/36, 30.6%) and ultrasound (US)/contrast-enhanced ultrasound (CEUS) (6/36, 16.7%). Three studies developed non-imaging models, and one combined CT and MRI. In within-study comparisons, multimodal models generally showed better discrimination than unimodal approaches. Peritumoral, habitat-based, and multiphasic strategies appeared promising. However, external validation was reported in only 6/36 studies (16.7%), calibration and decision-curve analysis were inconsistently reported, and most studies had high risk of bias. Conclusions: AI-driven models show potential to predict early recurrence of HCC after curative-intent resection. Nevertheless, evidence remains limited by methodological heterogeneity and restricted geographical diversity, while clinical utility remains inconsistently evaluated, and no model has yet been generalized in clinical practice. Prospective multicenter studies with standardized outcomes, transparent reporting, and external validation are needed for clinical implementation. Full article

Reliable detection of small agricultural targets is fundamental to precision crop protection, phenotyping, yield estimation, and robotic intervention. Typical examples include detecting aphids such as Aphis gossypii, whiteflies such as Bemisia tabaci, planthoppers such as Nilaparvata lugens, and other tiny pests on sticky traps or crop canopies for early warning, identifying crop-like weed seedlings for site-specific herbicide spraying, locating early disease lesions for targeted treatment, and detecting young fruits, flowers, or wheat heads for yield estimation and robotic manipulation. Agricultural small-object detection differs from generic small-object detection because target visibility is jointly determined by pixel area, physical size, imaging distance, ground sampling distance, canopy structure, biological similarity, and task-specific intervention requirements. Existing reviews have summarized agricultural object detection or general small-object detection, but they rarely connect agricultural failure modes with detector-level mechanisms and reproducible evaluation practices. This review addresses this gap through a mechanism-oriented synthesis of agricultural small-object detection. First, we revisit the limitations of the COCO-style 32²-pixel threshold and propose an agricultural scale-reporting framework that combines pixel area, physical scale, relative image occupancy, and acquisition geometry. Second, we organize recent methods according to the mechanisms by which they address detail loss, scale shift, occlusion, dense distributions, foreground–background confusion, localization uncertainty, and edge-deployment constraints. Third, we summarize public datasets, quantitative evaluation metrics, reporting checklists, and real-device deployment evidence to support fair and field-oriented comparison. Finally, we identify future directions in multimodal sensing, foundation-model adaptation, label-efficient learning, and hardware-aware optimization. By linking agricultural scene characteristics, detector mechanisms, and evaluation requirements, this review aims to provide a more actionable framework for developing robust small-object detection systems in precision agriculture. Full article

Food allergy is an increasingly prevalent global health condition characterized by immune-mediated reactions to dietary antigens and a substantial clinical burden. Growing understanding of IgE-mediated mechanisms has highlighted the central role of type 2 inflammation, effector-cell activation, and impaired immune regulation. These advances have prompted the development of disease-modifying therapies beyond allergen avoidance. This narrative review summarizes recent advances in the therapeutic management of IgE-mediated food allergy. A structured PubMed search was performed to identify clinical trials, randomized studies, and meta-analyses published within the last five years. Both allergen-specific and non-allergen-specific interventions were evaluated. Current evidence supports oral immunotherapy as the most effective strategy for increasing reaction thresholds and inducing desensitization in peanut, milk, and egg allergies. However, safety concerns remain, and sustained unresponsiveness after treatment discontinuation is achieved inconsistently. Sublingual and epicutaneous immunotherapy show improved safety but lower efficacy. Modified allergen approaches, including baked milk and processed peanut products, may improve tolerability and facilitate immune modulation in selected patients. Biologic therapies, particularly anti-IgE agents, demonstrate efficacy both alone and when combined with immunotherapy. Emerging approaches include peptide vaccines, DNA immunization, microbiome-targeted interventions, and early dietary modulation. These strategies may improve durable immune tolerance through personalized, mechanism-based therapeutic approaches. Future progress will depend on optimizing safety, identifying predictive biomarkers, and integrating multimodal approaches to achieve durable immune tolerance. Full article

Background: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults and remains associated with poor prognosis despite multimodal treatment. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation and redox imbalance, has recently emerged as a potential therapeutic vulnerability in glioma. This review summarizes current knowledge on the molecular regulation of ferroptosis in glioma and discusses its implications for tumor progression, therapeutic resistance, and translational targeting. Methods: A structured narrative review of the literature was conducted using PubMed/MEDLINE, Scopus, and Web of Science databases. Experimental, translational, and clinically relevant studies investigating ferroptosis-related mechanisms and therapeutic strategies in glioma and GBM were qualitatively analyzed. Results: Ferroptosis in glioma is regulated by interconnected pathways involving iron metabolism, phospholipid remodeling, oxidative stress, and antioxidant defense systems, particularly the SLC7A11–glutathione–GPX4 axis. Additional protective mechanisms mediated by FSP1 and DHODH, together with regulatory networks involving NRF2, ATF4, p53, and hypoxia-related signaling, contribute to adaptive resistance to ferroptosis. Increasing evidence indicates that ferroptosis interacts bidirectionally with the glioma tumor microenvironment and may exert both antitumor and immunosuppressive effects. Preclinical studies further suggest that ferroptosis induction may enhance the efficacy of temozolomide, radiotherapy, and immunotherapy, although clinical translation remains limited by tumor heterogeneity, blood–brain barrier penetration, and resistance mechanisms. Conclusions: Ferroptosis represents a biologically plausible and therapeutically promising target in glioma. Improved understanding of ferroptosis regulation, tumor microenvironment interactions, and biomarker-guided therapeutic strategies may support the future development of more effective treatments for GBM. Full article