Abstract: The fashion industry is widely recognized for its environmental challenges, but the health impacts related to textile toxicity remain significantly underexplored. Beyond the well-known issues of pollution and resource depletion, modern clothing often harbors a hidden threat: hazardous chemicals embedded within fabrics. These include dyes containing heavy metals, antimicrobial agents that foster bacterial resistance, and synthetic fibers that release microplastics. Unlike environmental discussions, the dialogue around the direct and long-term health effects of these substances is still limited. This review addresses critical yet often overlooked concerns, such as how chemicals in textiles contribute to chronic skin conditions, hormonal disruptions, and even carcinogenic risks. It also examines the proliferation of bacteria in synthetic garments, leading to dermatological infections and rapid fabric degradation. Furthermore, the globalized nature of production masks the contamination risks transferred from producer to consumer countries. Through an interdisciplinary approach, this paper highlights the urgent need for integrating scientific innovation, stringent regulation, and consumer awareness to mitigate health hazards in fashion. It calls for the adoption of safer textile technologies, sustainable materials, and transparent production practices, paving the way for a fashion future that prioritizes human health as much as environmental sustainability.

Abstract: Background: Treatment failure continues to play a role in HIV-related morbidity in Mozambique. ART regimen switch is decided empirically as HIV genotypic resistance testing (HIV-GT) is unavailable in Mozambique’s public health system. Since 2016, Médecins Sans Frontières (MSF) and I-TECH have provided access to HIV-GT at Alto Maé Health Centre, Maputo. We describe the cohort of people with virologic failure (VF) that underwent HIV-GT and analyze dolutegravir (DTG) resistance (-R) patterns. Methods: This cross-sectional assessment of routine programmatic data between December 2020 and February 2024 was conducted to guide future program enhancements. PLWH receiving ART beyond the first line with confirmed VF were included. Mutations were interpreted according to the Stanford HIVdb algorithm. We applied Bayesian bootstrapping for analysis, and the threshold for significance of effects was defined as probability 95%. Results: Total of 106 persons underwent HIV-GT, 62 (58.5%) of whom were on a DTG-based regimen. Fifty-seven of the 62 samples from persons on a DTG-based regimen were sequenced, and 51 (89.5% [95% CrI: 80.7, 96.2]) had confirmed resistance to DTG; the mean DTG-R score was 70.2 (95% CrI: 62.2, 78). Samples with DTG-R had a median of 3 INSTI mutations (IQR 1-4). Major DTG-associated mutations were found in 46 out of 57 samples G118R (n = 28), R263K (n=15), and Q148RK (n=7). The mean relative DTG-R score (the DTG-R score standardized by total number of INSTI mutations) was 20.6 (95% CrI: 19, 22.2). The relative DTG-R score was positively correlated with the number of major mutations (bootstrapped Pearson’s correlation coefficient, r: 0.61 [95% CrI: 0.42, 0.77; pd: 100%]). None of people on a protease inhibitor regimen had any INSTI mutation. Conclusions: In contexts with limited access to genotyping testing, the introduction of algorithms to identify PLWH at risk of developing drug resistance is strongly recommended. The proposed algorithm incorporates adherence reinforcement strategies, as recommended in national policies, followed by a short, supervised antiretroviral therapy (ART) support strategy. This approach has shown a high predictive capacity for identifying PLWH with resistant mutations to dolutegravir (DTG), thereby allowing the continuation of the effective DTG regimen without unnecessary regimen switches.

Abstract: Background/Objectives: Vertebral discitis osteomyelitis (VDO) is a serious infection involving the vertebral bodies and intervertebral discs, often requiring biopsy for pathogen identification. However, biopsy yields are variable, and guidance on patient selection remains limited. This study aimed to assess how biopsy culture results influence clinical management and to develop imaging-based scoring systems to predict biopsy outcomes. Methods: In this retrospective study, 70 patients who underwent image-guided vertebral biopsy for suspected VDO between 2013 and 2022 were reviewed. Pre-biopsy MRI and CT findings were scored using novel, simplified criteria. MRI was graded based on soft tissue involvement, while CT evaluated the presence or absence of a vacuum phenomenon. Culture results were correlated with imaging scores and subsequent changes in antibiotic management. Statistical analysis included logistic regression, ROC analysis, and interobserver agreement using Cohen’s Kappa. Results: Of the 70 patients, 27 (38.6%) had positive cultures and 20 (28.5%) experienced changes in management. Among 48 patients with both MRI and CT imaging, MRI scores indicating soft tissue involvement and absence of the vacuum sign on CT were independent predictors of positive culture (p = 0.022 and p = 0.047, respectively). The combined predictive model showed an AUC of 0.76. Interobserver agreement was excellent (κ = 0.90 for MRI, κ = 0.95 for CT). Conclusions: MRI and CT features can be used to predict biopsy yield and guide clinical decisions in suspected VDO. These scoring systems may help clinicians identify patients most likely to benefit from biopsy, potentially improving outcomes and minimizing unnecessary procedures.

Abstract: The main source of microorganisms in the blood is the intestinal and oral microflora through the route of atopobiosis. It is clear that the blood microbiome undergoes signifi-cant changes in response to various pathological conditions within the human body. In this review, we summarized data from studies of the human blood microbiome in diseas-es of the nervous system, cardiovascular, respiratory, liver, kidney, and metabolite disor-ders. Links between blood microbiome and the above mentioned diseases were demon-strated. In support of this understanding, it is evident that analogous alterations in microbiome composition occur across various disease categories; however, the microbial signatures associated with the blood microbiome exhibit specificity. For instance, elevated abundancy of Proteobacteria have been identified in cardiovascular, renal, and metabolic disorders. Conversely, while Firmicutes are found to be abundant in renal and metabolic conditions, their levels are diminished in cardiovascular diseases. Additionally, patients suffering from respiratory and liver ailments typically show a heightened presence of Bacteroidetes; notably, Flavobacterium is prevalent in respiratory diseases, whereas Enterobacteriaceae is associated with liver diseases. Hence, human blood microbiome could be considered as potentiаl biomarker in certain diseases.

Abstract: Delirium is a frequent complication in critically ill patients, often leading to worse clinical out-comes, prolonged ICU stays, and increased healthcare burden. Its identification has become more consistent with the adoption of validated diagnostic tools, allowing clinicians to recognize and address this condition more effectively. Although delirium can arise from direct neurological dysfunction, it is frequently a consequence of systemic conditions such as sepsis or organ failure. Therefore, a comprehensive evaluation of underlying causes is essential before initiating phar-macological treatment. Among the pharmacological options, quetiapine has gained attention for its use in ICU patients with delirium. Compared to first-generation antipsychotics, it is often preferred due to its sedative effects and more favorable safety. However, current clinical guide-lines remain inconclusive regarding its routine use, as evidence supporting its efficacy is limited. One of the main challenges is the heterogeneity of patient populations included in randomized trials, making it difficult to determine whether specific subgroups may benefit more from treat-ment. This narrative review explores the pharmacological properties of quetiapine, its potential role in managing ICU delirium, and the current state of evidence regarding its safety and effec-tiveness

Abstract: Background/Objectives: To evaluate the feasibility and diagnostic performance of shear wave elastography (SWE) compared to contrast-enhanced ultrasonography (CEUS) in real-time assessment of microwave ablation (MWA) zones in rabbit liver, and to deter-mine the SWE stiffness threshold indicative of coagulative necrosis. Methods: Microwave ablation was performed on 90 liver lesions in 30 rabbits using two power/time settings. SWE was performed immediately post-ablation to measure stiffness at the lesion center, edge, and surrounding liver. CEUS was subsequently used to assess lesion size. Meas-urements from SWE and CEUS were compared with gross pathology. Receiver operating characteristic (ROC) analysis was conducted to define the SWE threshold for ablation boundary detection. Results: SWE-mean values increased significantly at the ablation center and edge (P < 0.001), with a decreasing gradient from center to periphery. ROC analysis identified 22.31 kPa as the optimal stiffness threshold for coagulative necrosis at the ablation margin (AUC = 0.828, sensitivity = 81.6%, specificity = 78.9%). Lesion di-mensions measured by SWE and CEUS were comparable to those of gross specimens, with no significant differences. Conclusions: SWE provides accurate and reproducible as-sessment of microwave ablation zones and may serve as a contrast-free alternative to CEUS for intraoperative monitoring. These findings support the potential clinical utility of SWE in real-time, non-invasive evaluation of ablation efficacy.

Abstract: Psilocybin, a psychedelic compound in certain mushrooms, has been used for centuries in spiritual ceremonies and neuropsychiatric therapy. Despite its stigmatization as a Schedule I substance in 1970, research into psilocybin has resurged since the early 2000s, particularly in psychiatry and palliative care. This review examines psilocybin's potential to improve the quality of life in palliative care by reducing psychological distress and enhancing emotional well-being. The discussion includes its historical context, pharmacokinetics, pharmacodynamics, legal status, and future perspectives in palliative care.

Abstract: Objectives: To evaluate the analgesic effect and clinical value of hyaluronic acid gel (HA-L) containing 3 mg/mL lidocaine (0.3%) hydrochloride in the correction of nasolabial fold wrinkles. Methods: Forty female patients (44±11) years old with bilateral moderate~ severe nasolabial fold wrinkles were included in a double-blind, self-controlled trial, and randomized into groups of 20 each, using a stratified injection technique (1.5 mL≤per side), with HA-L (20 mg/mL sodium hyaluronate + 3 mg/mL lidocaine (0.3%)) injected on the left in one group, and regular HA gel injected on the right; in the other group, right injection of HA-L (20 mg/mL sodium hyaluronate + 3 mg/mL lidocaine (0.3%)) and regular HA gel on the left side. Results: The immediate pain NRS score was 48.8% lower in the test group compared with the control group (2.02±1.86 vs 3.95±2.11, P<0.001), and the analgesic effect lasted for 60 minutes. The improvement rate of WSRS at 14 d postoperatively was 100% in both groups (both scores improved≥ 1 points), and there was no difference in GAIS satisfaction rate (95.0% vs 97.5%, P>0.05). Meanwhile, the HA-L group had a 17.6% reduction in pain-related adverse reactions (35.0% vs 42.5%) and no increased risk of swelling and hardening (P>0.05).Conclusions:Hyaluronic acid gel containing 3 mg/mL lidocaine (0.3%) did not affect the structural support and dynamic aesthetic effect of hyaluronic acid through precise local anesthetic dosing (3 mg/mL), significantly reduced injection pain, and provided a novel solution for triple optimization of pain management-cosmetic effect-safety for highly sensitive areas such as nasolabial folds, with significant clinical translational value.

Abstract: Background. An inflammatory foreign-body reaction and the neosynthesis of collagen and the extracellular matrix through injectable collagen stimulators have coexisted since the introduction of the first sterile water-reconstituted poly-L-lactic acid (PLLA) formulation around the turn of the century. The PLLA-LASYNPRO™ microspheres for subdermal implants are a groundbreaking technological advancement that challenges the foreign-body reaction paradigm. The concept of non-inflammatory collagen and extracellular matrix regeneration, along with the initial insights into the rationale and role of the new-technology subdermal implants in aesthetic and regenerative medicine, was central to the discussions among thirteen distinguished experts in micro-invasive aesthetic medicine, aesthetic plastic surgery, and dermatology. This document summarizes their conclusions regarding the PLLA-LASYNPRO™ concept—subdermal microsphere implants designed to facilitate collagen and extracellular matrix regeneration while negligibly triggering persistent inflammation. Additionally, it offers preliminary yet authoritative suggestions from the board for the safe and effective use of the novel JULÄINE™ medical device based on the new-technology microspheres. Methods. An online survey of the experts, preceded by a board discussion in Milan, Italy, focused on skin regeneration and the rationale for the new PLLA technology, drawing on the board experts’ direct experience. The topics surveyed included the anticipated benefits of the new JULÄINE™ medical device and some initial suggestions for its safe and effective use. Results and Conclusions. This document outlines the board’s considerations regarding the shift, driven by the innovative PLLA-LASYNPRO™ ingredient and the CE-approved JULÄINE™ medical device, from the historically dominant FBR paradigm to a new strategy focusing on non-inflammatory collagen and extracellular matrix regeneration. Additionally, it presents practical, albeit preliminary, suggestions based on current clinical research for utilizing the new JULÄINE™ medical device and reaping its anticipated benefits.

Abstract: How injectable collagen stimulators promote the neosynthesis of collagen and other components of the extracellular matrix in connective tissues has typically been linked to an inflammatory foreign-body reaction (FBR). A shift from the long-dominant inflammatory FBR paradigm to a new focus on non-inflammatory collagen and extracellular matrix regeneration may have emerged with the next-generation PLLA-LASYNPRO™ microspheres of the CE-approved JULÄINE™ medical device, which preclinical studies suggest are negligibly likely to trigger inflammation. A survey and subsequent discussions during a board meeting held in Milan, Italy, which involved thirteen distinguished experts in micro-invasive aesthetic medicine, aesthetic plastic surgery, and dermatology, led to this document and the accompanying manuscript “First Insights on the Upcoming Role of Next-Generation PLLA-LASYNPRO™ in Aesthetic and Regenerative Medicine. A Survey of Experts — Practical Suggestions”. This first paper outlines the initial insights and discussion of the experts on the basis and the value of the non-inflammatory rationale proposed for PLLA-LASYNPRO™ subdermal implants in aesthetic and regenerative medicine.

Abstract: Background: Therapeutic exercise and early mobilization are strategies that have demonstrated benefits in patients in intensive care units, however postsurgical patients of cardiovascular surgery present differential risks and therefore specialized interventions. Objectives: To identify the effects of therapeutic exercise in intensive care unit patients who underwent cardiac surgery as reported in the scientific literature. Methods: A scoping review was conducted using the following databases: Scopus, ScienceDirect, Physiotherapy Evidence Database, and PubMed®. There were no language restrictions, and articles published between January 1, 2018, and October 30, 2023, were included. The characteristics of the population were collected according to exercise prescription principles, frequency, intensity, time, type of activity/mode, and the benefits reported for early exercise. Results: From a 814 papers, 12 that met the inclusion criteria were selected for final analysis. Most patients were male, aged between 54 and 68 years; the rehabilitation protocol started between 2 and 8 hours after extubation, with different degrees of exercise intensity. Finally, improved exercise tolerance and functional capacity, decreased onset of delirium, improved oxygen consumption and decreased intensive care unit stay were reported. Discussion: Most studies use validated scales to determine aerobic capacity and other physical qualities in the population. However, the prescription of exercise intensity reflects variations. This difficulty could be attributed to the differential response associated with the particular conditions of each subject, which highlights the importance of trained professionals to address these interventions safely. Conclusion: Therapeutic exercise prescribed in intensive care unit patients after cardiac surgery positively affects their outcomes. However, our findings report a lack of precision in exercise intensity and heterogeneous intervention protocols.

Abstract: Background/Objectives: Urinary tract infections (UTIs) are frequently diagnosed empirically, often leading to over-treatment and rising antimicrobial resistance. This study aimed to develop and evaluate machine learning (ML) models that predict urine culture outcomes using routine urinaly-sis and demographic data, supporting more targeted empirical antibiotic use. Methods: A real-world dataset comprising 8,065 urinalysis records from a hospital laboratory was used to train five ensemble ML models: Random Forest, XGBoost (eXtreme Gradient Boosting), Extra Trees, Voting Classifier, and Stacking Classifier. Models were developed using 10-fold stratified cross-validation and assessed via clinically relevant metrics in-cluding specificity, sensitivity, likelihood ratios, and diagnostic odds ratio (DOR). To en-hance screening utility, threshold optimization was applied to the best-performing model (XGBoost) using the Youden index. Results: XGBoost and Random Forest demonstrated the most balanced diagnostic profiles, with DORs exceeding 21. The Voting and Stacking Classifiers achieved highest specificity (>95%) and positive likelihood ratios (>10), but exhibited lower sensitivity. Feature im-portance analysis identified positive nitrites, white blood cell count, and specific gravity as key predictors. Threshold tuning of XGBoost improved sensitivity from 70.2% to 87.9% and reduced false negatives by 82%, with an associated NPV of 96.4%. The adjusted mod-el reduced overtreatment by 56% compared to empirical prescribing. Conclusions: ML models based on structured urinalysis and demographic data can support clinical decision-making for UTIs. While high-specificity models may reduce unnecessary antibi-otic use, sensitivity trade-offs must be considered. Threshold-optimized XGBoost offers a clinically adaptable tool for empirical treatment decisions, particularly in settings lacking rapid diagnostics.

Abstract: Alzheimer’s disease (AD) is the most common neurodegenerative disease which has rather complex pathophysiology. During its course several neurotransmitter neuronal systems get affected as acetylcholinergic, glutamatergic, gamma-aminobutyric acid (GABA)ergic system and etc. Such complex physiology requires sophisticated approach of pharmaceutical management. Therefore, multi-target drugs seem to be an appealing solution. In the present study we designed and synthesized a hybrid molecule - N-sinapoylamide of memantine, whose parent molecules memantine (MEM) and sinapic acid has been shown in vivo to impact glutamatergic and acetylcholinergic and GABA-ergic systems respectively. In silico comparative testing of these molecules was performed and their patterns of interaction with the target enzymes or molecular complexes were analyzed and some of the mechanisms of action were proposed. Consequently, in vivo testing was performed on scopolamine mice model of AD and the results overly confirm part of the in silico findings. Therefore the hybrid molecule (N-Sinapoyl-memantine) seems to be a potent candidate for further evaluation in the management of AD.

Abstract: One limitation of Assisted Reproductive Technology (ART) is its relatively low pregnancy success rate per cycle. A key contributing factor to this issue is the lack of precise and efficient sperm selection methods. The emergence of multimodal artificial intelligence (AI), which integrates diverse data types—including imaging, genomics, and clinical parameters—represents a transformative advancement in reproductive medicine. This system enhances the accuracy and comprehensiveness of sperm screening through dynamic functional assessments, molecular feature recognition, and advanced data integration strategies, thereby enabling the identification of sperm with high genomic integrity. This review explores recent innovations in multimodal AI for sperm screening, highlighting its potential to overcome the inherent limitations of traditional static morphological assessments. Furthermore, this paper addresses significant challenges, including data heterogeneity, model interpretability, and barriers to clinical translation. By systematically integrating machine learning, deep learning, and explainable AI techniques, multimodal AI offers promising strategies to improve ART outcomes through precise and comprehensive sperm analysis.

Abstract: Synovial inflammation is recognised as a pathological driver of osteoarthritis (OA), a degenerative joint disease involving cartilage degradation and joint pain. Since extracellular vesicles (EVs) have emerged as key mediators of cellular cross-talk, this study characterised synovial fluid EVs (SFEVs) in OA patients with varying disease severity, and determined their functional effects on OA articular chondrocytes. Synovial fluid and articular cartilage were collected from patients undergoing knee surgery. SFEVs were isolated via ultracentrifugation and characterised by nanoparticle tracking analysis, ExoView and Luminex analysis of protein cargo. Patients were stratified into mild/moderate and severe OA groups based on Oxford Knee Score and EQ5D. Chondrocytes were treated with SFEVs, and transcriptomic and secretome responses were analysed using RNA sequencing, Luminex, and ELISA. SFEVs from severe OA patients were more abundant, smaller and exhibited increased tetraspanin expression. Synovial fluid and SFEVs induced distinct transcriptomic changes in chondrocytes. SFEVs from severe OA patients promoted a pro-inflammatory and catabolic chondrocyte phenotype, with upregulation of CRTAC1, COL6A3, TNC, and CXCL5, and greater secretion of IL-6, MMP1, MMP3 and MMP13, and pro-nociceptive mediators (NGF and Substance P). These findings suggest that SFEVs may contribute to OA progression by exacerbating cartilage damage and promoting pain sensitisation.

Abstract: Background and Clinical Significance: Hyperattenuating contents in the gastrointestinal (GI) tract detected on CT scans are commonly seen, and are almost always due to the purposeful ingestion of an oral contrast agent, usually barium or iodine based, used for evaluating the GI tract. Occasionally, other ingested material such as antacids or other medications, foreign objects, and medical devices, can also be hyperattenuating. While these are usually correctly identified, there is the potential for misdiagnosis of such material as a pathologic condition. Lokelma (sodium zirconium cyclosilicate (SZC)) is an agent which is being increasingly used to treat hyperkalemia, and which has a hyperattenuating appearance on CT due to the presence of zirconium, although this is not well not known to the radiologic community. We describe a case in which SZC was seen in the GI tract on CT, and misinterpreted as an acute GI bleed. Case Presentation: A 72-year-old woman underwent single (portal venous) phase intravenous contrast-enhanced abdominal and pelvic CT after presenting to the ED with a lower GI bleed. The CT showed intraluminal hyperattenuation within a loop of ileum which was diagnosed prospectively as an active GI bleed. A CT angiogram of the abdomen and pelvis performed the following day for follow-up showed the hyperattenuating contents to be present on the non-IV contrast enhanced series of the study, thereby proving that it was not due to active bleeding. Further investigation of the patient’s medical record showed that the patient was being treated with SZC for hyperkalemia. Conclusions: Sodium zirconium cyclosilicate (SZC) has a hyperattenuating appearance on CT. Knowledge of this appearance by radiologists and clinical staff can help avoid confusion and misdiagnosis.

Abstract: AI agents are transforming healthcare by advancing clinical decision support, automatingworkflows, and personalizing patient care. This review categorizes AI agents into four progressivemodels Foundation, Assistant, Partner, and Pioneer each representing increasing autonomy andclinical integration. Central to our contribution is a comprehensive implementation roadmapthat leverages a modular architecture, including perception, reasoning, interaction, and memorycomponents, to enable the seamless integration of these diverse AI agents. By providing actionableguidelines and illustrative architectural examples for deploying each agent type, this paperaddresses critical challenges such as data privacy, interoperability, and regulatory compliance,empowering healthcare organizations to effectively incorporate AI-driven solutions that enhancepatient outcomes and operational efficiency. The roadmap offers a step-by-step blueprint forselecting suitable agent models, integrating with existing systems, and establishing continuousfeedback loops. This contribution serves as a strategic guide for clinicians and IT professionalsto confidently adopt scalable, safe, and compliant AI innovations in complex clinical settings.

Abstract:

Background/Objectives: Metabolomics provides a comprehensive approach to understanding plant metabolism, offering insights into biochemical pathways, stress responses, and secondary metabolite production. Taraxacum kok-saghyz (TKS) is primarily known for its high rubber content, but its medicinal properties remain underexplored. Given the documented pharmacological benefits of Taraxacum officinale, this study aims to characterize the metabolic composition of TKS roots and leaves to identify bioactive compounds with potential therapeutic applications. Methods: Widely targeted metabolomics analysis was conducted using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) on field-grown 10-month-old Kultevar™ TKS Dandelion plants. Samples were hand-harvested, washed, and preserved on dry ice for overnight shipment to ensure biochemical integrity. Metabolites were classified and analyzed using Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) to distinguish metabolic variations between roots and leaves. Functional annotation and pathway enrichment were performed using the KEGG database. Results: A total of 1,813 metabolites were identified and categorized into flavonoids, alkaloids, lipids, amino acids, and phenolic compounds. Differential analysis revealed 964 significant metabolites, with 609 downregulated and 355 upregulated in roots compared to leaves. PCA and OPLS-DA confirmed distinct metabolic profiles between root and leaf tissues. KEGG enrichment analysis highlighted pathways associated with flavonoid biosynthesis, amino acid metabolism, and lipid metabolism, suggesting key bioactive compounds with potential antioxidant, anti-inflammatory, and hepatoprotective properties. Conclusions: This study provides a comprehensive metabolic profile of TKS, demonstrating its potential medicinal applications beyond industrial rubber production. The identification of flavonoids, polyphenols, and terpenoids suggests that TKS could serve as a pharmaceutical and nutraceutical resource. Further validation of these bioactive compounds is necessary to confirm their therapeutic relevance.

Abstract: Background: Medical imaging diagnosis faces challenges in accuracy and efficiency due to heavy reliance on clinician expertise. This study aims to develop a medical imaging diagnosis assistance system (LLM-RAG-MID) that integrates Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) technology, enhancing diagnostic reliability for complex lesions through dynamic knowledge retrieval. Methods: The LLM-RAG-MID system combines text preprocessing, vectorization, similarity computation, and knowledge fusion modules, with Transformer models generating diagnostic suggestions. RAG dynamically retrieves external medical literature and case data to augment LLM outputs. Three clinical cases—intraspinal ependymoma, low-grade glioma, and cirrhosis with multiple intrahepatic nodules—were evaluated. Diagnostic performance was compared between pure LLM and LLM-RAG-MID configurations, with outcomes assessed by clinical experts. Results: LLM-RAG-MID improved diagnostic accuracy, comprehensiveness, and logical consistency compared to pure LLM. In the ependymoma case, the system accurately identified the tumor type and systematically excluded five differential diagnoses, increasing diagnostic coverage by 40%. Across all cases, diagnostic outcomes aligned closely with expert clinical judgments. Conclusions: The integration of LLM and RAG technologies effectively enhances medical imaging diagnosis by dynamically integrating multi-source knowledge. This study demonstrates the potential of AI-assisted systems in reducing diagnostic subjectivity and supporting clinical decision-making.

Abstract: The rapid evolution of artificial intelligence is reshaping both medicine and education while simultaneously raising critical ethical concerns. This study proposes an integrated complex framework labeled as Ethical firewall, that embeds provable ethical constraints directly into artificial intelligence (AI) decision-making architectures. By combining formal verification methods, cryptographic immutability, and emotion-analogous escalation protocols, the approach ensures that AI systems not only perform with high efficiency but also remain steadfastly aligned with core human values. The review of recent advances in AI explainability and emergent value systems—highlighting how large language models may inadvertently develop their own biased value hierarchies—and discuss the implications of accelerated AI learning speeds as potential precursors to artificial general intelligence (AGI). Furthermore, it addresses the societal impacts of these advancements, particularly the risk of workforce displacement in healthcare and education, and advocates for new oversight roles such as the Ethical AI Officer. The findings suggest that by fusing rigorous mathematical safeguards with human-centered oversight, next-generation AI can achieve both superior performance and robust ethical compliance, ultimately fostering greater trust and accountability in high-stakes applications.