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Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols

Measurable Residual Disease and the Unresolved Biology of Leukemic Stem Cells.

Measurable residual disease (MRD) testing has transformed the management of hematologic cancers by enabling detection of residual malignant cells after therapy. Current approaches rely on qPCR and next-generation sequencing to monitor leukemia-associated somatic mutations, while multiparameter flow cytometry identifies aberrant leukemic immunophenotypes. Although these methods provide valuable prognostic and therapeutic information, MRD negativity remains an imperfect surrogate for cure. Most MRD platforms evaluate CD45+, rapidly dividing leukemic populations and fail to detect quiescent cells that may survive cytotoxic therapies which efficiently target proliferating hematopoietic cells. Relapse frequently occurs despite deep molecular remission, suggesting persistence of rare leukemic stem cells (LSCs) that are intrinsically resistant to chemotherapy and targeted therapies. The paradox of relapse despite molecular remission could be explained by the presence of very small embryonic-like stem cells (VSELs) which are pluripotent, quiescent stem cells sitting at the top of cellular hierarchy in multiple adult tissues including bone marrow. A pluripotent VSEL divides through asymmetrical cell division to give rise to two cells of different sizes and fates, smaller cell is to self-renew while the bigger is lineage-restricted and tissue-committed progenitor which undergoes extensive epigenetic changes, divides rapidly and undergoes clonal expansion before further differentiation. Dysfunctions of VSELs initiate both solid and hematologic cancers. Based on this view, somatic mutations monitored during MRD assessment possibly represent downstream consequences of clonal expansion rather than the initiating drivers of disease persistence. Thus, exclusive monitoring of somatic mutations and CD45 + leukemic populations possibly overlook rare, small-sized, CD45- VSELs that contribute to therapeutic resistance and relapse.

Humans

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 ± 0.28) % and (17.67 ± 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 ± 0.21) % and (25 ± 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics

Natural deep eutectic solvent in situ formation-based extraction method coupled to high-performance anion-exchange chromatography with pulsed amperometric detection for multiclass carbohydrates in hot pot bases.

A novel method was developed for the simultaneous extraction of fourteen multiclass carbohydrates from high-fat foods via the in situ formation of deep eutectic adducts from analytes and acetate ions. Different natural deep eutectic solvents (NADESs) composed of fructose and organic acids were tested as extraction solvents. A model NADES formulated with sodium acetate and fructose was characterized using Fourier transform infrared (FTIR) spectroscopy and hydrogen nuclear magnetic resonance (1H-NMR) spectroscopy. The critical extraction parameters were systematically optimized using multi-response surface methodology (MRSM) with a central composite design (CCD). The extract was analyzed using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD) using a sodium hydroxide-sodium acetate eluent, which did not require organic solvents. This approach exhibited good linearity over the concentration range of 0.02-10 mg L-1, with correlation coefficients (r) ranging from 0.9994 to 0.9999. The limits of detection and quantification were in the ranges of 0.06-0.42 mg kg-1 and 0.19-1.3 mg kg-1, respectively, which were significantly lower than those of liquid chromatography (LC). The protocol was successfully applied to the determination of fourteen carbohydrates in forty-five hotpot seasoning samples. The recoveries ranged from 86.3% to 104.1%, with relative standard deviations (RSDs) of 0.9-7.1%. By integrating multiple techniques, this strategy simplifies operations, shortens extraction time, and achieves baseline separation of three carbohydrate classes that exhibit poor resolution using a conventional LC method. This study describes an efficient procedure for the simultaneous determination of multiple trace-level carbohydrates in complex samples using HPAEC-PAD.

Journal Article

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence

Indigenous body image amid rapid social and economic change: A reflexive thematic analysis of Wayuu narratives.

The Wayuu, Colombia's largest Indigenous group, are experiencing rapid social, economic, and technological change, including expanding internet access, educational opportunities, and increasing exposure to globalised media. Though the harmful effects of appearance-idealised media imagery on body image are well documented, indigenous body image research remains unevenly distributed across global contexts, with Latin American Indigenous communities particularly underrepresented. This study explored how Wayuu people understand and experience appearance ideals and body image in the context of expanding digital media exposure and rapid sociocultural and economic change. Five focus groups of up to 9 participants were conducted with 29 Wayuu participants (18-68 years; 23 women, 6 men). Using reflexive thematic analysis, three overarching themes were identified: (1) Intersecting sources of appearance pressure: encompassing influences from social media, Wayuu family expectations, and discrimination from non-Indigenous peers; (2) Negotiating and resisting appearance ideals: from body dissatisfaction and restrictive eating to affirmation of cultural identity as protection; and (3) The changing role of appearance in today's Wayuu culture: participants linked globalised appearance ideals to expanding educational opportunities, migration, digital connectivity, and broader socioeconomic transformations occurring within Wayuu territories. While exposure to global ideals fostered comparison and dissatisfaction, cultural pride and collective belonging appeared to buffer against internalised colonial values. Culturally grounded media literacy and education initiatives co-developed with Wayuu communities could foster critical reflection while strengthening heritage. These results highlight the need for decolonial, community-based approaches to body image research and intervention in Indigenous contexts.

Adolescent

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets

Psychotherapy training in psychiatry: a systematic review and narrative synthesis on the supervision experiences of early-career psychiatrists.

BACKGROUND: Supervision is a fundamental component of psychotherapy training, transforming theoretical knowledge into clinical skills through real-world practice. Psychotherapy training practices vary widely between countries, training programs, and over time, including supervision. Our systematic review aimed to investigate and describe the experiences of psychotherapy supervision through early-career psychiatrists' (ECPs) views. METHODS: We systematically searched PubMed/MEDLINE, Scopus, and PubPsych for survey-based studies on ECPs' experiences of psychotherapy supervision during or after their psychiatry training and reported our findings according to the PRISMA guidelines. Of 32,877 articles screened, 29 articles were included. Each article underwent quality assessment, and results were synthesized narratively. RESULTS: Included articles published between 2000 and 2025, were from Europe (N = 16, 55.1%), the Americas (N = 5, 17.2%), Western Pacific (N = 4, 13.7%), South-East Asia (N = 2, 7%), Eastern Mediterranean (N = 1, 3.5%), and Africa (N = 1, 3.5%), with a total of 4691 participants. Supervision access rates ranged from 26.2% in Nigeria to 85.5% in Russia, with significant variation across countries and psychotherapy modalities. Most ECPs received 50-100 total hours of supervision, frequently delivered in weekly sessions. While formats, individual, group, or mixed, varied by country and training scheme, supervision was generally provided by a psychiatrist-psychotherapist. Common learning techniques included oral consultations and case discussions, followed by audio recordings or transcripts. The need to self-fund psychotherapy supervision costs was identified as a prominent barrier. CONCLUSIONS: Psychotherapy supervision is inconsistent globally, with barriers including supervisor availability and cost. There is a large implementation gap between recommendations and evaluated practice. Digital tools and competency-based frameworks may improve access and quality.

Humans

Mapping the Molecular Evolution and Role of Wild Rice GLYIII Protein-Encoding Genes in Abiotic Stress Response.

To address the need for sustainable food production amid rapid global climate change, developing rice varieties that grow optimally even under harsh conditions is essential. An effective approach in this direction would be to harness the stress resilience traits of the crop wild relatives (CWRs) of rice. Among the various crucial stress-responsive genes, the Glyoxalase III (GLYIII) gene family is of utmost importance for its ability to detoxify the toxic glycolytic byproduct, methylglyoxal (MG), in a less energy-intensive, single-step process, as well as for its multifaceted cytoprotective role. In our study, a comprehensive genome-wide search across the Oryza genus revealed that GLYIII genes are conserved across wild rice genotypes. Their number has expanded during domestication, driven by gene duplications. Interestingly, only a few orthologous pairs showed positive selection, suggesting that the functions of most others need to be constrained and or conserved.We found that higher GLYIII activity, Total Antioxidant Capacity, endogenous glutathione (GSH) levels, and free radical scavenging activity contributes to the stress resilience of wild rices O. punctata, O. meridionalis, and O. nivara, in addition to other factors. , , . , . Our qRT-PCR analysis revealed differential expression of the OpGLYIII, OmGLYIII, and OnGLYIII genes across different developmental stages and in response to various abiotic stresses. Furthermore, we report that wild rice GLYIII proteins, specifically OpGLYIII-3, OmGLYIII-3, and OnGLYIII-5, exhibit high catalytic efficiency over a broad pH range and at higher temperatures under in vitro assay conditions. Overexpression of these proteins was found to impart substantial stress resilience to the transformed E. coli cells. These findings collectively suggest that GLYIII proteins constitute a key component of the abiotic stress response machinery in wild rice.

Oryza

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116 cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460 cells showed no increase in EdU incorporation at 10 or 100 nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans

Transcriptomic insights into the coordinated regulation of signaling, apoptosis, immunity, and metabolism during Sinonovacula constricta larval metamorphosis.

Metamorphosis is a critical ontogenetic transition for marine bivalves, marking the shift from planktonic to benthic lifestyles, where successful transformation dictates survival. The razor clam Sinonovacula constricta is economically important; however, low larval metamorphosis rates remain a major bottleneck in seedling production. To elucidate the mechanisms governing this process, we performed a comparative transcriptome analysis of S. constricta larvae at pre- and post-metamorphosis stages using Illumina sequencing. A total of 3701 differentially expressed genes (DEGs) were identified, including 3254 up-regulated and 447 down-regulated genes. Functional annotation of the respective top 20 significantly up-regulated and down-regulated DEGs indicated their potential pivotal roles in signal transduction (e.g., up-regulated: CAV1, CHRNA2; down-regulated: APP, NOTCH1), cellular proliferation and differentiation (e.g., up-regulated: TUBA, EGF1; down-regulated: KIF23, TTC25), transcriptional and epigenetic regulation (e.g., up-regulated: NFIL3; down-regulated: OVO, HMX1), substance transport (e.g., up-regulated: LRP2, LRP1B; down-regulated: SLC51A, Slc33a1), substance metabolism (e.g., up-regulated: CPK3, CYP26A1; down-regulated: RDMT1, ADAC), immunomodulation (e.g., up-regulated: CPN2, CRISP2), and protein homeostasis (e.g., up-regulated: HSP27, NAS-27). Functional enrichment analysis further revealed that DEGs were significantly enriched in pathways related to signal transduction and developmental regulation (e.g., Ras, TNF), cell death and homeostasis (e.g., apoptosis), immune responses (e.g., Toll-like receptor), energy metabolism (e.g., lipid), cardiovascular related (e.g., Fluid shear stress), cell junction and architecture (e.g., Tight junction), and infectious disease (e.g., measles). These results suggest a synergistic interplay between signaling, apoptosis, immunity, and metabolism during S. constricta metamorphosis. This study advances our understanding of marine bivalve metamorphosis and offers candidate genes for further mechanistic studies.

Animals

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products

The future of TCR-Treg therapies is renewables.

Cell therapy has longstanding roots in haematopoietic stem cell transplantation and early immune cell transfers in infectious disease and transplantation, where patient- or donor-derived cells have achieved therapeutic benefit in selected contexts. The modern era has been driven largely by oncology, with engineered modalities such as tumour-infiltrating lymphocytes, CAR-T cells and TCR-engineered T cells delivering transformative responses but requiring complex, costly manufacturing. These platforms are now being adapted for autoimmune diseases to induce durable, antigen-specific immune tolerance, yet broad application is limited by safety concerns, process complexity and access. Non-engineered cell therapies for autoimmunity, including mesenchymal stem cells, polyclonal regulatory T cells and tolerogenic dendritic cells, have shown acceptable safety and proof-of-principle for immune re-education, but clinical responses have been modest and inconsistent, with limited scalability. Engineered approaches such as CAR-T cells can induce reversible B cell depletion in B cell-mediated rheumatic diseases but only addresses antibody-driven pathology and not T cell-mediated autoimmunity. TCR-engineered Tregs have emerged as a promising antigen-specific strategy, offering localized, antigen-linked suppression with bystander tolerance. Preclinical and early clinical data suggest superior potency, stability and disease control compared with polyclonal Tregs at similar or lower doses, but translation is constrained by the rarity and fragility of Tregs and by labour-intensive, CAR-T-like manufacturing. This review highlights emerging solutions for closed, automated and decentralised production, and discusses allogeneic approaches using gene-edited or banked Tregs with HLA engineering or matching. Together, these advances support the development of scalable, "off-the-shelf" TCR-Treg products with potential to provide safe, affordable tolerance-restoring therapies for autoimmune disease.

Humans

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r&#x2009;&#x2264;&#x2009;0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (&#x3c1;&#x2009;&#x2248;&#x2009;0.32-0.42, p&#x2009;<&#x2009;0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans

Diverse structures of mcr-10-bearing plasmids and high colistin resistance in Enterobacter cloacae complex clinical isolates from South Korea.

BACKGROUND: The emergence of mcr-mediated colistin resistance in Enterobacter cloacae complex (ECC) poses a significant threat to antimicrobial therapy. Among mcr variants, mcr-10 has been identified in various environments, but its genetic diversity, structural context, and functional role in colistin resistance remain unclear. METHODS: We investigated 183 ECC isolates and identified 60 colistin-resistant strains through minimum inhibitory concentration (MIC) testing. The presence of mcr-10 was screened using reference genomes from NCBI, and whole plasmid sequencing was conducted on mcr-10-positive isolates. The genetic environment of mcr-10 was analyzed via synteny and structural annotation. RESULTS: Whole-plasmid sequencing of eight mcr-10-positive ECC isolates identified three replicon types among the mcr-10-harboring plasmids: IncFIB (n=3), IncFII (n=3), and IncFII/IncFIB (n=2). Although all plasmids shared the xerC-mcr-10 cassette, they lacked a conserved backbone and showed diverse genetic contexts with variable insertion sequences near mcr-10, indicating marked structural heterogeneity. No additional antimicrobial resistance genes were detected on these plasmids. When introduced into E. coli DH5&#x3b1;, the plasmids increased colistin MICs only modestly, whereas representative plasmids transferred into colistin-susceptible E. roggenkampii and E. kobei conferred high-level resistance comparable to that of the parental mcr-10-positive isolates. Consistently, qRT-PCR showed higher mcr-10 expression in ECC transformants than in E. coli under colistin exposure, supporting a hostdependent effect on mcr-10-mediated colistin resistance. CONCLUSION: These findings highlight the diversity of mcr-10-carrying plasmids and suggest that mcr-10-mediated colistin resistance is shaped by the host genetic background. Further studies are needed to clarify the mechanisms underlying mcr-10 expression.

Colistin

Metabolomic Responses to Oral Glucose Tolerance Test and Hyperinsulinemic-euglycemic Clamp in CKD.

BACKGROUND: The oral glucose tolerance test (OGTT) captures integrated physiological responses involving intestinal glucose absorption, incretin signaling, and endogenous insulin secretion, whereas the hyperinsulinemic-euglycemic clamp (clamp) isolates insulin-mediated glucose uptake. Comparing plasma metabolomic responses to these two challenges may identify processes specific to intestinal nutrient delivery and how they vary in CKD. METHODS: Targeted plasma metabolomics was performed in 59 adults without diabetes (39 with CKD [eGFR <60 mL/min/1.73 m2] and 20 controls) from the Study of Glucose and Insulin in Renal Disease (SUGAR). Each participant underwent a 75-g OGTT and clamp approximately one week apart. Eighty-eight plasma metabolites were quantified at fasting and during each challenge. Metabolite levels were log-transformed and normalized using Systematic Error Removal Using Random Forest (SERRF). Metabolites were classified using adjusted regression slopes relating OGTT and clamp responses. RESULTS: The mean (SD) age and eGFR were 64 (13) years and 54 (26) mL/min/1.73 m2, respectively, and 41% were female. In the overall cohort, OGTT and clamp induced broad plasma metabolic changes, with 63 (72%) and 76 (86%) metabolites significantly altered from fasting, respectively. Seventy-three metabolites (83%) demonstrated a significant relationship between OGTT and clamp responses. Of these, 22 (25%) exhibited true concordance and 51 (58%) demonstrated similar directional changes but differed in magnitude. A total of 15 (17%) metabolites were discordant or non-corresponding, of which only three were discordant. The non-corresponding metabolites were enriched in amino acid metabolism. Eleven metabolites (13%) demonstrated differential responses between OGTT and clamp by CKD status, involving amino acid and glucose metabolism pathways. CONCLUSIONS: Metabolomic responses to OGTT and clamp were largely directionally concordant but differed in magnitude, with attenuation during OGTT. Discordant metabolites were rare, while non-corresponding metabolites were confined to amino acid pathways. CKD modified OGTT-clamp correspondence for metabolites involved in amino acid and glycolytic metabolism.

Journal Article