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Mendelian randomisation for rheumatology: beyond hype-what it's good for, what it can't do, and how to read it critically.

Mendelian randomisation (MR) has become abundant in the literature, with variation in quality and frequent overinterpretation of causality. This creates a problem for clinical readers, reviewers, and editors: some MR studies can sharpen causal thinking, prioritise drug targets, and challenge misleading observational claims, whereas others are little more than automated exposure-outcome scans with causal claims disproportionate to the evidence. MR can strengthen causal inference when randomised trials are impractical and conventional observational studies are vulnerable to confounding, reverse causation, or selection bias. In rheumatology, credible MR can contribute to questions about disease aetiology, modifiable risk factors, therapeutic target validation, adverse-effect anticipation, and phenotype validation. However, its interpretation depends on whether the exposure is plausibly instrumentable, whether the genetic instruments are biologically defensible, whether assumptions are interrogated in ways appropriate to the design, and whether findings are triangulated with clinical, observational, experimental, and mechanistic evidence. Instead of recapitulating all methodological issues of MR, this review aims to help rheumatologists distinguish robust MR from weak or overinterpreted analyses quickly. We provide an accessible framework for reading and triaging MR studies in rheumatology. Papers that use poorly justified instruments, treat medication use as drug-target evidence, interpret genetic liability as diagnosis, rely on mechanical sensitivity analyses, ignore prior evidence or ask no clinically meaningful question can often be passed over by readers. The goal is not to discourage MR in rheumatology, but to raise the standard; useful MR should clarify causal reasoning rather than simply generate another statistically significant association.

Journal Article

Lifestyle interventions to prevent gestational and type 2 diabetes among migrant women from low- and middle-income countries: a systematic review.

Migrant women from low- and middle-income countries (LMICs) living in high-income settings experience disproportionately high risk of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM). This review aimed to identify and synthesise culturally adapted lifestyle interventions for preventing or managing GDM and T2DM among migrant women from LMICs, focusing on intervention components, cultural adaptation strategies, and behavioural and metabolic outcomes. Five databases (PubMed, Embase, Scopus, CINAHL, Cochrane Central) were searched using Preferred Reporting Items for Systematic reviews and Meta-Analysis 2020 guidelines. Eligible studies included experimental designs involving lifestyle interventions delivered to migrant women from LMICs in high-income countries, reporting outcomes related to GDM or T2DM targeting behaviour change. Data were synthesised narratively; study quality was appraised using RoB2 for RCTs and a structured narrative approach for non-randomised designs. Certainty of evidence was evaluated using GRADE. Eight studies met the inclusion criteria. Sample sizes ranged from 28 to 641 participants. Intervention duration varied from 6 weeks to 12 months. Most interventions incorporated atleast one culturally tailored component, such as bilingual delivery, culturally adapted dietary education, or community-based engagement. Improvements were reported across dietary behaviours, physical activity, glycaemic measures, or diabetes-related knowledge; however, effect sizes were modest and inconsistent. Interventions combining dietary modification, physical activity, and culturally adapted delivery demonstrated greater improvements than exercise-only or digital-only programmes. Overall certainty of evidence ranged from low to moderate. Culturally adapted, multi-component lifestyle interventions show promise for improving behavioural and metabolic outcomes among migrant women from LMICs; however, the evidence base remains limited.

Humans

Investigation of ACE gene polymorphism and serum ACE activity in relation to alopecia areata among Iraqi patients.

BACKGROUND: Alopecia areata (AA) is a multifactorial disorder with immune dysregulation and genetic susceptibility, affecting 0.5-2% globally. OBJECTIVE: This study investigated angiotensin converting enzyme (ACE) gene insertion /deletion (I/D) polymorphism and serum ACE activity in Iraqi AA patients and their association with inflammatory cytokines (interleukin [IL]-17) and nutritional markers to understand disease progression. METHODS: This case-control study included 50 AA patients (Male and Female) and 35 healthy controls. ACE gene polymorphism (rs1799752) was analyzed using real-time polymerase chain reaction (qPCR) with high-resolution melting (HRM) analysis. Serum IL-17 levels were determined by enzyme-linked immunosorbent assay (ELISA), and biochemical markers were measured using an automated analyzer. RESULTS: ACE gene polymorphism (rs1799752) showed non-significant genotype distribution between patient and control groups (p&#xa0;>&#xa0;0.05), though a trend toward DD genotype enrichment was observed in patients. Serum ACE levels were significantly higher in patients versus controls (p&#xa0;<&#xa0;0.0001) with high diagnostic performance. ACE correlated positively with IL-17 (P&#xa0;<&#xa0;0.0001) and negatively with vitamin D3 and zinc (P&#xa0;<&#xa0;0.0001). Female patients had significantly higher ACE levels than males (P&#xa0;<&#xa0;0.01). CONCLUSIONS: ACE emerges as an immunometabolic hub in AA pathogenesis, integrating inflammation with nutritional deficits, suggesting its potential as a biomarker and therapeutic target.

Humans

Reference genome of the Californian trapdoor spider Aptostichus stephencolberti Bond 2008 (Araneae: Mygalomorphae: Euctenizidae).

We present a reference genome assembly for the trapdoor spider Aptostichus stephencolberti. This species, described in 2008, is endemic to the highly fragmented coastal dune habitats of Northern California from Monterey to the San Francisco Bay Area. Trapdoor spiders are ideal taxa for landscape scale genomic studies owing to their extreme site fidelity and limited dispersal capabilities; these same characteristics make them prone to extinction. Genomic studies of species like A. stephencolberti can reveal novel areas of endemism and high conservation value that may not be evident in species with wider ranges and greater dispersal capabilities. As part of the California Conservation Genomics Project, we constructed the A. stephencolberti reference genome from high quality long-read sequences, scaffolded with proximity ligation Omni-C data. The primary assembly comprises 551 scaffolds spanning 3.63 Gbp, a scaffold N50 of 62.2 Mbp and BUSCO completeness of 95.6%. We estimate 52 chromosomes yet find no (TTAGG)n telomer repeats. Expanding the telomeric repeat search finds an ancestral loss of the repeat from all spiders. Automated annotation using the NCBI refseq pipeline and RNAseq data from whole adults finds 14,067 genes with a BUSCO annotation completeness of 95.56%. Repeat annotation identified 77% of the genome to be interspersed repeats. This resource, the first for family Euctenizidae will facilitate future study and resulting conservation actions of A. stephencolberti and other Aptostichus sp. populations associated with the rapidly changing California coastal dune ecosystem.

Aptostichus stephencolberti

The Long Road to Long-Acting: What Oral PrEP and CAB-LA Teach Us About Scaling Lenacapavir.

Despite significant biomedical advances, human immunodeficiency virus (HIV) remains a persistent global health crisis, with over 40 million people affected as of 2023, two-thirds of whom live in the World Health Organization (WHO) African Region. However, from an HIV prevention perspective, the more urgent concern is the continued occurrence of approximately 1.3 million new infections annually, particularly in sub-Saharan Africa and in settings where incidence is stable or increasing. This commentary explores the evolving landscape of HIV prevention, focusing on the trajectory of oral pre-exposure prophylaxis (PrEP), long-acting injectable cabotegravir (CAB-LA), and the newly emerging lenacapavir. While oral PrEP opened new possibilities, adherence challenges have limited its impact. CAB-LA demonstrated superior efficacy but encountered access, cost, and delivery barriers that restricted uptake. Lenacapavir, offering 6-monthly subcutaneous dosing with &#x2265;&#xa0;99.9% efficacy in trials, holds the potential to overcome these hurdles. As of May 2026, lenacapavir had received regulatory approval in 17 countries, including several African nations, while regulatory reviews remained ongoing in multiple additional countries, reflecting the rapid global expansion of access to this long-acting HIV prevention option. However, its success depends on clinical promise, timely licensing, affordability, and integration into health systems. Drawing from real-world lessons of oral PrEP and CAB-LA, this paper argues that a proactive, coordinated rollout of lenacapavir could dramatically expand prevention reach. With global stakeholders aiming for 3 million users by 2028 and strategic licensing in 120 countries, the groundwork is in place. The recent release of WHO guidance recommending lenacapavir as an additional PrEP option further strengthens this momentum. Yet, equitable delivery, user-centred models, and strong policy backing will be critical. Ultimately, long-acting PrEP is not just a clinical breakthrough; it is a test of health systems' ability to deliver innovation at scale.

Humans

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n&#x2009;=&#x2009;688) and an independent prospective test cohort (n&#x2009;=&#x2009;193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' &#x3ba; of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7&#xa0;s to 9.9&#xa0;s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

Humans

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques

Generation of spCAS9 expressing human mesenchymal stem cell line to study gene function during osteoblast differentiation.

Human bone marrow-derived stromal cells (hMSCs) are a great resource for studying how genes influence cell fate and differentiation into various cell types like osteoblasts, adipocytes, and chondrocytes, among other cell types. However, genetic manipulation of primary hMSCs has been challenging due to their short lifespan and cellular senescence after limited passaging. Their low and unstable transfection efficiency also complicates gene delivery or inactivation, hindering long-term functional studies. The limited lifespan has been effectively solved by immortalizing hMSCs with telomerase reverse transcriptase (hMSCs-TERT). The use of these cells is ideal for functional studies of osteoblast and adipocyte differentiation through genetic manipulation, providing a stable and reliable model. Here, we have engineered a stable CAS9 expressing hMSC-TERT cell line (hMSC-TERTCAS9) via lentiviral transduction. The constitutive expression of spCas9 enables efficient and reproducible gene editing. We demonstrate the potential of these hMSC-TERTCAS9 cells for generating gene disruptions using plasmid delivery of guide RNAs as a fast and efficient strategy for targeted genome editing. The edited cells can be sorted and expanded as single cells to obtain homogenous clonal cell lines with mono- as well as bi-allelic gene deletions, a crucial step for producing reliable experimental results. We further validate this cell line as a powerful tool for studying gene function during hMSC proliferation and differentiation, providing 3 distinct examples of its utility. Through the generation of indels, single-cell sorting, and clonal selection, we have efficiently inactivated the vitamin D receptor and created both larger (256 nucleotides) gene disruptions in Forkhead box protein O1 and precise removals of a small genomic sequence (73 nucleotides) coding for microRNA MIR675. This novel hMSC-TERTCAS9 cell line represents a significant advancement, offering a stable, efficient, and versatile platform for advanced genetic studies, high-throughput screening, and the creation of reliable cellular disease models.

CRISPR-Cas9

Aneurysmal subarachnoid hemorrhage care in a middle-income public healthcare system: A real-world neurocritical care cohort.

BACKGROUND AND PURPOSE: Although aneurysm treatment capacity has expanded worldwide, outcomes after aneurysmal subarachnoid hemorrhage (aSAH) remain strongly influenced by neurocritical care (NCC) delivery, referral pathways, and access to specialized treatment. Contemporary data describing real-world aSAH care in resource-limited healthcare systems remain scarce. We aimed to characterize treatment patterns, NCC delivery, complications, and outcomes in a large Brazilian public referral center. METHODS: This retrospective cohort study included consecutive adults with confirmed aSAH admitted between June 2018 and March 2022 to a high-volume Brazilian tertiary referral center. Only patients admitted within five days of symptom onset were included. Demographic, clinical, radiological, treatment, complication, and outcome data were extracted from institutional records. Primary outcomes were in-hospital mortality and 3-month functional outcome assessed by the modified Rankin Scale (mRS). RESULTS: Seventy-four patients were included. Disease severity was high, with 45% presenting WFNS grades 4-5, 73% modified Fisher grade 4 hemorrhage, and 64% hydrocephalus. Endovascular treatment was performed in 73% of cases, and median time from admission to aneurysm treatment was 1&#xa0;day. Despite early treatment capability, only 28% of patients were admitted to an ICU within 48&#xa0;h, while 38% never received ICU care. Delayed cerebral ischemia occurred in 43%, radiologic vasospasm in 58%, ventriculitis in 22%, and infectious complications in 57%. External ventricular drainage was required in 42%, and vasoactive drugs were used in 85%. In-hospital mortality was 42%, and 66% had unfavorable 3-month outcomes (mRS 4-6). CONCLUSIONS: This real-world cohort highlights the substantial neurocritical care burden of aSAH in a middle-income public healthcare system. Despite timely access to definitive aneurysm treatment, patients experienced frequent neurological and systemic complications, emphasizing that contemporary aSAH care extends well beyond aneurysm occlusion.

Humans

Development of a cell-based nanoluciferase reporter system for high-throughput screening of HBV cccDNA inhibitors.

Hepatitis B virus (HBV) persistence is sustained by the viral covalently closed circular DNA (cccDNA) minichromosome, which remains a major barrier to curative antiviral therapies. The lack of reliable quantitative cccDNA detection methods and surrogate markers has hindered efforts to target cccDNA in antiviral high-throughput screening (HTS). Here, we established a novel inducible cccDNA-dependent nanoluciferase (NLuc) reporter cell line, designated HepBLE12, by inserting an in-frame 11-amino acid split-NLuc HiBiT tag into the precore (pC) coding region of an HBV transgene. The resulting 1.3-kDa HiBiT tag on pC serves as the detection module of the split NLuc system, generating quantitative luminescence upon high-affinity complementation with the cognate 18-kDa LgBiT subunit in cell lysates. Notably, the HiBiT assay enables direct detection of intracellular HiBiT-pC protein rather than secreted HBeAg, providing a reporter signal more closely linked to cccDNA activity. HepBLE12&#x202f;cells exhibited inducible and robust viral DNA replication, and the cccDNA-dependent HiBiT signal was validated under diverse experimental conditions that modulate cccDNA formation or transcription. We further miniaturized the assay to a 384-well format and optimized key parameters following standard HTS assay development practices. The assay was successfully automated and demonstrated excellent performance in a multi-day variability study and a pilot screen, with signal-to-background (S/B)&#x202f;&#x2248;&#x202f;9, coefficient of variance (CV)&#x202f;<&#x202f;10%, and average Z-factor value of 0.74, exceeding canonical HTS quality benchmarks. Together, the HepBLE12 cell-based HTS platform provides a robust and practical tool for identifying inhibitors targeting HBV cccDNA.

Hepatitis B virus

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans

Assessing comorbidities and predicting risk: A primer for APRNs.

Today's clinical environments are rife with tools designed to comprehensively account for medical complexity and comorbidities while predicting risk for a host of adverse health-related outcomes. Therefore, it is imperative that advanced practice registered nurses (APRNs) understand the structure and function of these tools, their similarities and differences, their limitations, and strategies for appropriate incorporation into practice. This article offers a practical overview for APRNs, emphasizing clinical implications and guidance for aligning assessment tools with the clinical population of interest to improve care delivery, quality, and patient outcomes.

Humans

Comparative genomics and full-length transcriptome profiling of wing morphs in Tetrix grossus (Orthoptera: Tetrigidae).

Wing polymorphism represents a paradigmatic dispersal-reproduction trade-off, yet its molecular basis remains uncharacterised in the phylogenetically distant pygmy grasshoppers (Tetrigidae). Here we integrate comparative genomics across ten orthopteran species with full-length transcriptomics of long-winged (FL) and short-winged (FS) Tetrix grossus. OrthoFinder recovered 118 orthogroups specific to T. grossus. Against a backdrop of pronounced gene-family contraction (36 expansions versus 222 contractions; net -186, mirrored at the ancestral Tetrix node, +37/-140), we identified an ancestral, Tetrix-specific expansion of hormone-regulation (12 genes; fold enrichment 7.93) and lipid/carbohydrate-metabolic families organised into syntenic clusters, alongside 513 positively selected genes enriched for integrin-mediated cell adhesion (6 genes), a process relevant to epithelial and appendage morphogenesis. Full-length transcriptomics of one long-winged (FL) and one short-winged (FS) adult female detected 7530 (FL) and 7515 (FS) expressed genes, with 794 FL- and 776 FS-restricted transcriptome-derived SNP-associated genes. The FL morph was enriched for an EGFR/Ras-Rho developmental-patterning axis and neuromuscular flight genes, whereas the FS morph was enriched for insulin/peptide-hormone response and growth-regulatory loci. Overall, we present genomic resources and testable hypotheses concerning the evolution and regulation of wing morphs in Tetrigidae rather than a validated genetic architecture of wing-morph determination.

Animals

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans

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

Artificial intelligence-derived myocardial fibrosis on cardiac magnetic resonance for prognosis in cardiomyopathy: A systematic review of a sparse evidence base.

BACKGROUND: Myocardial fibrosis on cardiovascular magnetic resonance (CMR), assessed by late gadolinium enhancement (LGE) and parametric mapping, is an established predictor of adverse events in cardiomyopathy. We assessed whether artificial intelligence (AI) quantification of fibrosis adds independent prognostic value. METHODS: We searched six databases, a clinical-trials register, and a preprint server from inception to 13 June 2026. Eligible studies used AI to generate a fibrosis marker in adults with ischemic or nonischemic cardiomyopathy, with covariate-adjusted outcomes over &#x2265;12 months. Risk of bias was assessed using PROBAST, PROBAST+AI, and QUIPS. Fewer than three comparable studies precluded meta-analysis; certainty was rated using GRADE. RESULTS: Of 448 records (381 after de-duplication), 18 full texts were reviewed and two included, one peer-reviewed and one preprint. In an ischemic-cardiomyopathy registry (Ghanbari et al.; n = 216 analytic, 26 events), AI-derived dense LGE scar predicted arrhythmic events (univariable hazard ratio [HR] 2.35, 95% CI 1.33-4.15), and AI-derived but not manual scar improved discrimination beyond guideline criteria (area under the curve 0.63 to 0.68; p = 0.02). In a nonischemic dilated-cardiomyopathy preprint (Kim et al.; n = 347, 119 events), automated extracellular volume &#x2265;30% predicted cardiovascular death or heart-failure hospitalization (adjusted HR 2.00, 95% CI 1.32-3.03). Both were at high risk of bias, with data-derived thresholds and no external validation. CONCLUSIONS: Across only two studies, AI-derived fibrosis was independently associated with adverse cardiovascular events, but its added value over manual quantification remains unproven. Certainty was very low. The evidence base is sparse and not yet ready for clinical use.

Humans

Emergence of a Novel, Phenotypically Difficult-to-Detect Vancomycin-Resistant Enterococcus faecium Clone (ST117/CT7799).

A significant increase of vancomycin-resistant Enterococcus faecium (VREfm) infections was observed in South-Eastern Austria since 2024. The prolonged outbreak is caused by a novel vanB-VREfm clone (ST117/CT7799, "VREfmstyr"). This study characterizes the atypical difficult-to-detect resistance phenotype and assesses the genomic relatedness of the isolates. Patient and outbreak characteristics were investigated including whole genome sequencing of the isolates. Sensitivity of broth microdilution (BMD), gradient tests (GT), disk diffusion (DD), and automated susceptibility testing (VITEK2) was compared. The performance of commercial screening media was evaluated. From sporadic detections in early 2024 case numbers began to rise during the year. In 30/31 (97%) of all cases, intra-hospital transmission was considered likely and an association with invasive procedures was identified in most cases. Core genome multilocus sequence typing revealed only six allelic differences between VREfmstyr isolates collected in a 12-month period, all belonging to the E. faecium ST117/CT7799 lineage. BMD detected vancomycin resistance (MIC&#x2009;>&#x2009;4&#x2009;mg/L) in no more than 16/31 (52%) of isolates after 24&#x2009;h incubation, while GT and DD misclassified all isolates. Only prolonged incubation improved the performance of these assays. VITEK2 analysis, however, correctly classified all 31 isolates. Of four commercially available VRE-screening agars, only one was capable of detecting VREfmstyr after 24&#x2009;h incubation. The emergence and clonal dissemination of VREfm ST117/CT7799 reveals a serious diagnostic gap as commonly used diagnostic algorithms fail to reliably detect this resistance phenotype. Our findings should help to further evaluate the true geographical distribution and clinical significance of this novel VREfm clone.

Enterococcus faecium