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Redefining the real problem in psychedelic trials: Why fighting the Lessebo matters more than blinding integrity.

Imperfect blinding is not specific to psychedelic trials. In randomized trials, treatment allocation is frequently correctly guessed, yet blinding integrity is rarely assessed outside of psychedelic research and is generally not considered a barrier in regulatory evaluation. The intense debate in psychedelics may reflect a broader double standard affecting mental health research, when uncertainties arising from imperfect blinding are confounded by those linked to patient-reported outcome measures. Indeed, people living with mental disorders are often viewed as unreliable reporters, despite well-documented limitations of clinician-rated scales and the absence of robust biological markers of symptomatic change. Importantly, it is the maintenance of reasonable doubt of treatment allocation that sustains internal validity and ethical feasibility of placebo-controlled designs, rather than perfect blinding. Concerns about expectancy bias in psychedelic trials are closely tied to blinding debates. When allocation is inferred, expectations may cluster in the arm perceived as active or in stereotyped experiences and influence outcomes differently in active and control arms, leading to a risk of lessebo, a negative placebo effect due to the negative expectation related to receiving a placebo. However, we argue that an underrecognized mechanism of lessebo is disappointment. This risk may reflect insufficient clinical management of disappointment rather than pre-treatment expectation alone. We therefore propose shifting the emphasis from preserving inevitably imperfect blinding towards mitigating disappointment in both arms. Establishing non-stereotyped expectations prior to treatment through structured psychoeducation, strengthened therapeutic alliance, and realistic preparation would help avoid lessebo effects. Such strategies would enhance ethical rigor, interpretability, and the clinical usefulness of psychedelic trials.

Humans

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans

The effects of visuomotor training and tDCS stimulation on visuomotor integration and visual processing: an electrophysiological approach.

BACKGROUND: Visuomotor integration coordinates visual and motor cortical activity to produce goal-directed responses and can be indexed by Rolandic Mu-rhythm suppression and visual evoked potential (VEP) P100 parameters. Perceptual-motor training improves visuomotor performance, and transcranial direct current stimulation (tDCS) over primary motor cortex (M1) has been reported to enhance motor learning when paired with training. This study examined whether anodal M1 tDCS augments the effects of Senaptec visuomotor training in healthy adults. METHODS: Sixty participants were randomized to active anodal tDCS (five 10-minute sessions, 1 mA; n = 31) or sham (n = 29) over M1 immediately before each Senaptec training session; 53 completed all sessions and post-testing. Outcomes were Mu-suppression ratios, VEP P100 latency and amplitude, and Senaptec measures of visual sensitivity and visuomotor control. RESULTS: Active tDCS produced no augmentation of any outcome, with no significant group × time interaction for any measure, consistent across composite and task-level analyses. Training alone produced no change in Mu suppression or visuomotor control. By contrast, both groups showed significant training-related gains in visual sensitivity, including near-far quickness and stereopsis, accompanied by shorter P100 latencies and larger amplitudes, indicating more efficient early visual processing. CONCLUSIONS: A clear dissociation emerged: training produced robust improvements in early visual processing, whereas neither tDCS nor training altered sensorimotor (Mu) or visuomotor-control measures. The tDCS results should be interpreted cautiously given the modest dose and limited power to detect small effects, rather than as evidence of inefficacy. Tablet-based perceptual training enhanced visual processing independent of neuromodulation.

Humans

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals

Integrated proteomic and acetylomic analyses reveal the metabolic reprogramming associated with increased tylosin-equivalent concentration in Streptomyces xinghaiensis sf106-B1.

Deciphering the metabolic basis of high-yield antibiotic production in Streptomyces is crucial for strain optimization. Atmospheric and room-temperature plasma (ARTP) mutagenesis of Streptomyces xinghaiensis sf106 generated a mutant with a 30% increase in tylosin-equivalent concentration (μg/mL). 4D-FastDIA quantitative proteomics identified 279 differentially abundant proteins enriched in the Type I polyketide synthase (PKS) pathway, with increased abundance of key macrolide-biosynthesis-related proteins. Lysine-acetylome profiling identified 1152 differentially abundant acetylation sites and revealed altered acetylation of enzymes involved in fatty acid metabolism and the tricarboxylic acid (TCA) cycle, suggesting adjustments in central metabolism associated with acyl-CoA precursor availability and energy generation. Integration of proteomic and acetylomic data suggests coordinated changes in protein abundance and lysine acetylation associated with the increased tylosin-equivalent concentration. These results highlight candidate nodes for rational metabolic engineering of S. xinghaiensis.

Streptomyces

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical

Integrated widely targeted metabolomics and GC-IMS reveal dynamic flavor, nutritional, functional, and metabolic profiles in macadamia kernels during processing.

Different processing stages influence the color, flavor, and antioxidant activities of macadamia kernels. However, the biochemical mechanisms that occur during processing are not well known. This study integrated widely targeted metabolomics (UPLC-MS/MS) with GC-IMS to systematically characterize non-volatile and volatile compounds in macadamia kernels across key three sample groups: fresh kernels (FMN), low-temperature-dried kernels (DMN), and roasted kernels (BMN). A total of 622 non-volatile metabolites and 52 volatile compounds were identified. Low-temperature drying promoted the accumulation of phenolic acids and flavonoids, enhancing antioxidant capacity. Roasting degraded heat-sensitive nutrients but generated flavor compounds via Maillard reaction and lipid oxidation, shifting aroma from green to nutty notes. Nutritional assessment confirmed that roasting significantly reduced antioxidant activities and bile acid binding capacity. Pearson correlation analysis verified the key metabolite-antioxidant relationships. These findings provide critical insights into metabolic dynamics during nut processing and establish a scientific basis for optimizing thermal processing strategies.

Metabolomics

Integrative modeling of the genome structure and dynamics in fission yeast.

Genome organization in the nucleus is highly structured and dynamic. Recent advances in genomic technology have enabled the measurement of genome-wide architecture and locus-specific motion, yielding contact maps and live-cell trajectories. However, these outcomes are derived from different modalities and are not directly comparable, with their quantitative integration being a key challenge. Here we establish a genome-wide live-cell imaging platform in fission yeast Schizosaccharomyces pombe, tracking 131 chromosomal loci, along with the spindle pole body (SPB) and nucleolus, to construct a quantitative map of locus dynamics. By integrating these dynamics with contact data through polymer modeling of Hi-C data, we build a physics-based "digital twin" of the S. pombe genome consistent with the spatiotemporal dynamics of interphase chromatin. We validate it against genome-wide mobility patterns and known architectural features, including centromere and telomere clustering. The model also identifies distinct dynamical regimes: centromere- and telomere-proximal loci relax within [Formula: see text]150 s, whereas the remaining loci relax within [Formula: see text]70 s. We measure semiperiodic dynamics of SPB motion, including a characteristic peak near 225 s and [Formula: see text] fluctuations. We use the model with SPB-directed forcing to show how these low-frequency components propagate through the genome to drive genome-wide chromatin displacements. Together, this predictive physics-based modeling framework integrates genome structure and dynamics to reveal how nuclear mechanical driving forces shape chromosome motion, linking mechanically driven chromatin responses to genome maintenance and regulation.

Schizosaccharomyces

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans

Effects of Cognitive Behavioral Couple Therapy With Integrated Mindfulness on Mindful Attention, Depressive Symptoms, and Dyadic Adjustment in Low-Income Couples: A Pilot Randomized Clinical Trial.

Psychosocial distress can exacerbate marital conflict, maladjustment, and mental health vulnerability. This pilot randomized clinical trial examined cognitive-behavioral couple therapy (CBCT) integrated with mindfulness in low-income Brazilian couples (per-capita household income up to one minimum wage). Thirty-four participants (17 heterosexual couples) were randomized (independent computer-generated sequence) to an experimental (n&#x2009;=&#x2009;16) or waitlist control group (n&#x2009;=&#x2009;18). We assessed dyadic adjustment, mindful attention, marital social skills, and depressive symptoms (R-DAS, MAAS, IHSC, BDI-II) at baseline, post-treatment, and 3-month follow-up. The intervention was eight 80-min conjoint sessions plus daily home exercises. Time&#x2009;&#xd7;&#x2009;group effects favored the experimental group for dyadic adjustment, mindful attention, and depressive symptoms (all p&#x2009;<&#x2009;0.001,&#x2009;=&#x2009;0.20-0.37), but not marital social skills (p&#x2009;=&#x2009;0.14). Because two outcomes differed at baseline, effects were confirmed with baseline- and dependence-adjusted sensitivity analyses. These findings provide preliminary evidence that CBCT with mindfulness may benefit disadvantaged couples.

Adult

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

Tele-Oncology in the Post-Pandemic Era: Clinical Integration, Access Disparities and Medico-Legal Accountability.

PURPOSE OF THE REVIEW: Tele-health has evolved from a marginal tool confined to rural populations and selected follow-up programs into a structurally integrated component of modern cancer care. Prior to COVID-19, its adoption was constrained by regulatory fragmentation, non-uniform reimbursement, and licensure barriers. This narrative review evaluates the evolutionary integration of tele-health in oncology post-COVID-19, examines digital disparities across patient populations, and addresses the medico-legal implications of this integration, with the objective of providing a comprehensive and clinically actionable framework for the governance of virtual oncology care. RECENT FINDINGS: The pandemic acted as a global catalyst, driving telehealth to over 50% of oncology outpatient encounters in some settings, before stabilising post-pandemic at approximately 10-20% of consultations within hybrid care models. Evidence supports meaningful clinical benefits - improved access to specialist services, reduced travel burden, and sustained continuity of care - with outcomes comparable to in-person care in postoperative follow-up, symptom monitoring, and survivorship. However, persistent disparities in device availability, connectivity, and digital literacy disproportionately affect older, rural, and socioeconomically disadvantaged patients, raising the risk that geographic inequalities are replaced by technological ones. From a medico-legal standpoint, the remote modality does not modify the applicable standard of care, yet restricted physical examination and reliance on patient-reported data introduce risks of diagnostic delay and incomplete clinical assessment, with direct implications for professional liability, data protection under HIPAA and GDPR, cross-border licensure, and multi-party accountability across physicians, institutions, and technology providers. Tele-oncology has become a permanent structural feature of modern cancer care, offering demonstrable benefits in access, continuity, and patient satisfaction. Yet its integration has been uneven, its governance remains fragmented, and its medico-legal landscape is still evolving. Realising the full potential of virtual oncology care - equitably and safely - requires coherent regulatory frameworks, sustained investment in digital infrastructure, and explicit attention to the populations at greatest risk of being left behind.

Humans