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PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

An RPA-assisted homogeneous electrochemical DNA sensor for on-site eDNA detection toward early warning of crown-of-thorns starfish outbreaks.

Crown-of-thorns starfish (COTS) outbreaks seriously threaten coral reef ecosystems, while conventional monitoring approaches are time-consuming and often lack sufficient sensitivity for early warning. Existing electrochemical DNA sensors usually require complex electrode-surface immobilization procedures, which can lead to uneven probe distribution, significant steric hindrance, and poor stability. Meanwhile, the low concentration of environmental DNA (eDNA) in marine environments further complicates detection. To overcome these challenges, this study developed a homogeneous electrochemical DNA sensor assisted by recombinase polymerase amplification (RPA) for COTS eDNA detection. Target DNA was first amplified by RPA, and the amplification products were then hybridized in solution with capture probe (CP)-modified magnetic beads (MB) and biotin-labeled signal probe (SP) to form sandwich-structured MB complexes. These complexes were subsequently magnetically enriched and immobilized on the electrode surface for electrochemical signal readout. Under optimized conditions, the sensor displayed a linear response to COTS genomic DNA from 3.77 fg/μL to 1 ng/μL, with an LOD of 2.02 fg/μL and an LOQ of 3.77 fg/μL. The sensor was applied to Xisha Islands samples, and the results agreed with droplet digital PCR (ddPCR) (P > 0.05), demonstrating its potential for sensitive and reliable on-site COTS eDNA detection.

Animals↗

PubMed2026

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of ∼0.47 fM and a quantitative range of 1 fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

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↗

PubMed2026

Applications of metal-organic frameworks in smart packaging for food freshness indication: a comprehensive review.

Smart packaging is extensively studied for its multifunctional capabilities in antimicrobial activity, preservation, and atmosphere modification. Recently emerged metal-organic frameworks (MOFs) freshness-indicating packaging becomes a key research direction in smart packaging owing to its distinctive functions and physicochemical properties. As multifunctional materials, the unique porous structure and tunable properties of MOFs provide a distinctive approach for developing food packaging applications dedicated to food freshness indication. Existing MOFs-based smart packaging still faces potential safety risks and technical challenges in practical applications, and there remains a lack of integrated discussion that combines synthesis strategies, packaging design, optimization, and safety assessment. This review elaborates on the application of MOFs in freshness-indicating smart packaging, focusing on diverse MOFs synthesis strategies, the formats of smart packaging, types of indicator signals, and qualitative/quantitative analytical methods. It also delves into the methodology concepts of MOFs-based smart packaging and evaluates MOFs safety in food packaging by addressing potential risks. Studies show that MOFs-based smart packaging achieves qualitative and semi-quantitative analysis of food freshness through multiple signal modalities such as visible color change, fluorescence, and photothermal effects. This review emphasizes that safe MOFs design is critically important and should comply with the overall migration limit of <10 mg/dm2 specified in Regulation (EC) No 1935/2004, lanthanide element limit of <0.05 mg/kg, and FDA threshold of 1.5 μg/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging↗

PubMed2026

HPV Testing Versus Cytology for Cervical Cancer Screening Among Women 50 Years and Older: Evidence From the HPV FOCAL Randomized Controlled Trial.

Evidence on the comparative effectiveness of HPV testing versus cytology specifically in women aged ≥ 50 years who are approaching screening cessation remains limited. This analysis included 6471 women aged ≥ 50 at baseline screening in the HPV FOCAL randomized clinical trial. Women were randomly allocated to receive cytology (Control Group, n = 3248, 50.19%) or HPV testing (Intervention Group, n = 3223, 49.81%) at baseline, with co-testing at 48-month exit. We calculated incidence rates and risk ratios for CIN2+ detection over follow-up and compared missed lesions at exit by screening method. At the 48-month exit, CIN2+ detection was lower among HPV baseline-negative women than among those in the cytology group (1.61/1000 [95% CI, 0.52-3.76] vs. 3.15/1000 [95% CI, 1.51-5.78]; risk ratio, 0.51 [95% CI, 0.11-0.91]), reflecting higher baseline detection with HPV testing and fewer prevalent lesions at exit. Even with cytology re-screening at 2 years, 50% of CIN2+ cases were missed compared to 30% with HPV testing. After adjusting for age, education, smoking status, and lifetime sexual partners, the hazard ratio for CIN2+ comparing HPV to cytology was 0.44 (95% CI, 0.22-0.88). Among women aged ≥ 50 years, HPV primary screening was more effective than cytology at detecting CIN2+ lesions and was associated with a continued lower subsequent risk following a negative HPV test, supporting its use in cervical cancer screening programs in this age cohort.

Aged↗

PubMed2026

Suppression of HIV-1 replication in CEM-A cell cultures by trans-splicing group I introns targeting PAS/PBS sequences and conditionally expressing ΔN-Bax.

Anti-HIV group I introns containing antisense guide sequences directed against the HIV-1 primer activation signal and primer-binding site (PAS/PBS) were designed and evaluated. Because PAS/PBS sequences are present in the viral RNA species examined, these RNAs can serve as trans-splicing substrates. The introns were active against both artificial target RNAs and viral RNA generated during infection. Cleavage and degradation of targeted viral RNA may have contributed to suppression, whereas inclusion of a 3' exon encoding the proapoptotic protein ΔN-Bax was associated with increased programmed cell death and may have augmented suppression of viral replication. In cultured CEM-A cells, transgene expression of these introns markedly suppressed HIV-1 replication, with p24 levels falling below the assay detection limit in selected clones. RESULTS: RT-PCR and sequence analysis detected splice products containing the expected PAS/PBS junctions. In the dual-luciferase assay, intron expression reduced normalized Gaussia luciferase signal by approximately 70% relative to the negative control. Qualitative Annexin V imaging and caspase-3 assays were consistent with infection-dependent apoptosis after ΔN-Bax splice-product formation. Transient expression of each intron in HEK293T cells followed by infection with VSV-G-pseudotyped HIV-1NL4-3 at an MOI of 2 reduced p24 levels by approximately 50% at 4 days post-infection. Construct 128L produced the strongest RT-PCR band under the tested conditions and was selected for subsequent experiments. A canonical splice product and a low-abundance noncanonical splice product were detected; both involved the intended HIV-derived target RNA, although transcriptome-wide off-target splicing was not assessed. Heterogeneous transformed HEK293T populations showed an approximately 2-log10 reduction in p24. In selected clonal HEK293T and CEM-A lines, p24 was below the assay detection limit at the measured endpoints, including up to 90 days after infection in some CEM-A clones. CONCLUSIONS: PAS/PBS-targeting group I introns suppressed HIV-1-associated p24 production in the tested cell-culture models. Linking the introns to a ΔN-Bax 3' exon was associated with infection-dependent apoptosis and may further limit viral replication and spread. The use of highly conserved, functionally constrained target sequences may reduce the likelihood of escape, but viral evolution and transcriptome-wide off-target effects were not assessed. This conditional death-upon-infection strategy warrants further evaluation in primary-cell and in vivo models.

Humans↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Emerging techniques of CRISPR/Cas system in antiviral therapy and diagnostics: Applications, limitations, and translational perspectives.

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats) system is a versatile technology for developing antiviral medicines and editing viral genomes in both diagnostics and vaccine synthesis. Emerging insights into class 2 effectors, such as Cas9, Cas12, and Cas13, which target viral DNA and RNA, have revolutionized vaccines against viruses such as HIV, HPV, HBV, and EBV. Innovative diagnostic techniques such as SHERLOCK, DETECTR, and FELUDA have demonstrated system's diversity and accuracy in detecting the virus markers, supporting clinical decision-making, indicating adaptability and precision of CRISPR. This review critically evaluates CRISPR's role in RNA editing, emphasizing its importance for functional genomics and development of recombinant vaccines. Translational challenges are critically discussed, including off-target effects, delivery limitations, and ethical issues, for which unique approaches such as high-fidelity Cas variants, non-viral delivery systems, and bioethical frameworks are evaluated to address these limitations. This review also covers other social implications, such as accessibility and biosecurity risks, associated with CRISPR technologies Collectively, these advances underscore the transformative potential of CRISPR technologies in shaping next-generation antiviral diagnostics and therapeutics.

CRISPR-Cas Systems↗

PubMed2026

Beyond species trees: pervasive gene flow limits phylogenomic resolution in the diversification of Juniperus from the Qinghai-Tibet Plateau.

Understanding how lineages diversify despite persistent ancestral polymorphism and recurrent gene flow remains a central challenge in evolutionary biology. Juniperus distributed across the Qinghai-Tibet Plateau provide an ideal system for addressing this question because repeated geological uplift and climatic oscillations have likely promoted cycles of lineage divergence, range shifts, and secondary contact. Here, we combined approximately 1.08 million genome-wide SNPs from 164 individuals representing thirteen Juniperus lineages with phylogenomic datasets comprising 3,381 nuclear single-copy genes and nearly complete plastomes. We detected extensive phylogenomic discordance and cytonuclear incongruence across genomic datasets. Topology weighting, coalescent simulations, quartet-based tests, and analyses of gene flow and reticulation collectively support the interpretation that these patterns were shaped by the combined effects of prolonged incomplete lineage sorting and gene flow during lineage diversification. Ecological niche analyses further provide a spatial and climatic context in which environmentally similar lineages may have had greater opportunities for secondary contact during historical range shifts. Collectively, our results reveal that the evolutionary history of Qinghai-Tibet Plateau Juniperus is characterized by reticulate diversification rather than strictly bifurcating evolution, and demonstrate how genome-wide discordance can provide biological insights into the evolutionary processes underlying lineage diversification.

Gene Flow↗

PubMed2026

Incidence of silent cerebral lesions during pulsed field ablation for paroxysmal atrial fibrillation.

BACKGROUND: Radiofrequency catheter ablation (RFCA) is a first-line treatment for paroxysmal atrial fibrillation (PAF). Complications such as silent cerebral lesion (SCL) may occur during ablation. Pulsed field ablation (PFA) is a non-thermal method thatablates cardiac tissue via irreversible electroporation. Limited studies have reported the incidence of SCL during PFA, with highly variable results. However, randomized controlled trials (RCTs) remain scarce. The objective of this study was to compare perioperative SCL incidence between PFA and RFCA, and to identify risk factors for SCL during PFA. METHODS: In this prospective pilot RCT (ChiCTR2400088774), 62 patients with PAF were randomized 1:1 to undergo PFA or RFCA. Cerebral MRI (3.0 T) was performed preoperatively and 24-48h postoperatively. SCL was defined as a new acute brain lesion on MRI without neurological deficits. Baseline and surgical data of the patients were collected. RESULTS: SCL was detected post-procedure in 6.45% (2/31) in the RFCA group, 12.90% (4/31) in the PFA group. No statistically significant difference in the incidence of postoperative SCL was detected between the two groups (p = 0.67). Left atrium dimension (LAD), left atrial operation time (LAOT), left ventricular end-diastolic dimension (LVEDD), and total operation time (TOT) were significantly higher in SCL group than those in no-SCL group (p < 0.05) through univariate analyses. CONCLUSIONS: SCL incidence was 12.90% in the PFA group versus 6.45% in the RFCA group. While no statistically significant difference was detected between two groups, the numerically higher rate in the PFA group warrants larger studies to evaluate cerebral safety associated with PFA.

Humans↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Resistance versus concurrent training with three assigned protein targets in middle-aged and older women: a randomized 2 × 3 factorial trial.

BACKGROUND: Evidence is limited regarding whether assigned protein targets modify responses to resistance training (RT) alone or to the same RT program plus cycling (concurrent training [CT]) in middle-aged and older women. This randomized 2 × 3 factorial trial examined bioelectrical impedance analysis (BIA)-derived skeletal muscle mass (SMM; primary outcome), other body composition outcomes, muscular and functional performance, and cycle-derived estimated VO₂max. METHODS: In this randomized 2 × 3 factorial trial, 108 women aged 40-77 years were assigned to 12 weeks of supervised RT or CT (identical RT followed by cycling) and protein targets of 0.8, 1.6, or 2.2 g·kg-1·d-1. Baseline-adjusted ANCOVA tested training × protein interactions and marginal training and protein effects. Complete-case analyses included 83 participants. RESULTS: For SMM, no training-condition × protein-target interaction (p = 0.856), marginal protein-target effect (p = 0.726), or marginal training-condition effect (p = 0.273) was detected. CT had a lower baseline-adjusted week-12 BFP than RT (adjusted difference, -2.04 percentage points; 95% CI, -2.94 to -1.14; p < 0.001). RT had a higher baseline-adjusted week-12 leg-press estimated 1-RM than CT (CT - RT: -6.68 kg; 95% CI, -8.32 to -5.04; p < 0.001), whereas CT had a higher baseline-adjusted week-12 cycle-derived estimated VO₂max (adjusted difference, 4.53 mL·kg-1·min-1; 95% CI, 3.80 to 5.25; p < 0.001). No detectable marginal protein-target effects or training-condition × protein-target interactions were observed for the key secondary outcomes. CONCLUSIONS: No detectable differences in SMM or key secondary outcomes were attributable to assigned protein target. Compared with RT, CT favored estimated aerobic fitness and BFP, whereas RT favored leg-press strength. Because CT included additional cycling and greater exercise exposure, these differences cannot be attributed solely to training modality. Null protein findings do not establish equivalence among doses.

Humans↗

PubMed2026

Single-slice Functional Lung MRI During Metronome-Paced Tachypnea Detects Changes in Regional Ventilation Dynamics After a Single Dose of Dual Bronchodilator Treatment in COPD.

Dual long-acting bronchodilators are a standard treatment in chronic obstructive pulmonary disease (COPD), aimed at alleviating dyspnea, improving exercise tolerance, and preventing exacerbations. Metronome-paced tachypnea (MPT) offers a feasible alternative to exercise testing for the evaluation of dynamic hyperinflation (DH) in COPD. Because MPT can be performed during MRI, its combination with single-slice phase-resolved functional lung (PREFUL) MRI provides a promising approach to investigate changes in regional ventilation dynamics induced by DH. This approach was evaluated in a randomized, investigator-blinded, placebo-controlled, single-dose (SD) crossover trial with a two-week extension of once daily dual bronchodilator medication, in which patients with stable COPD underwent PREFUL MRI during resting tidal breathing (RTB) and during MPT. During RTB, no significant improvements in MRI-derived parameters were observed after SD treatment compared with placebo. During MPT, however, regional ventilation, flow-volume loop correlation, its defect percentage, and end-expiratory lung area improved significantly after SD treatment compared to the placebo scan (all p < 0.02). After multi-dose treatment, five out of six measured parameters improved during MPT, when compared to the baseline scan without bronchodilator treatment (all p < 0.03). In contrast to RTB, PREFUL MRI during MPT was able to detect changes in COPD patients already after SD treatment. The combination of MPT and PREFUL MRI represents a promising method to evaluate the effects of dual bronchodilators on regional ventilation dynamics and hyperinflation.

Humans↗

PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans↗