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PubMed2026

An Assessment of Reliability Estimation Methods for Binomial Health Care Quality Measures.

We evaluated the performance of commonly used methods for estimating the reliability of binomial health care quality measures using simulated datasets spanning a range of performance score means and variances, numbers of entities, and patient sample sizes. For each simulation, reliability was estimated for all selected methods and compared with the known true reliability derived from the simulation parameters, with methods assessed on their accuracy and precision. Logistic regression with reliability estimated on the outcome scale demonstrated the highest accuracy and precision among all methods evaluated. The widely used Adams beta-binomial method performed poorly, although a modification recommended by Nieser and Harris substantially improved its performance. These approaches are applicable only to binomial measures. Among methods that can be applied to both binomial and continuous measures, permutation resampling of the Spearman rank correlation coefficient was the most accurate and precise, outperforming other commonly used approaches. Overall, for binomial quality measures, logistic regression on the outcome scale is the preferred method for reliability estimation, followed closely by the modified beta-binomial approach, while for non-binomial measures, permutation-based Spearman rank correlation appears to be the most suitable method.

Reproducibility of Results↗
PubMed2026

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans↗
PubMed2026

Loneliness and Personality: Noise- and Bias-Free True Correlations Between Loneliness and the Big Five Personality Domains.

OBJECTIVE: While loneliness is intertwined with many mental and physical health problems, its origins are not yet well understood. We sought to better understand its link to personality in a large national cohort. METHODS: Combining self- and informant ratings in multiple samples, we conducted the largest study to date to examine loneliness' true correlations (rtrues) with the Big Five personality traits, free of single-method biases and transient and random errors. RESULTS: Across three samples (Estonian-speaking, N = 20,893; Russian-speaking, N = 762; English-speaking, N = 599), we found a strong relationship between loneliness and Neuroticism (rtrue = 0.60-0.70). Loneliness also had robust but much weaker associations with Extraversion (rtrue = -0.20 to -0.30), and only weak associations (rtrue = 0.10 to -0.20) with Agreeableness, Conscientiousness, and Openness. Collectively, the Big Five accounted for over 50% of loneliness variance. In a subsample, the associations were only slightly smaller longitudinally over approximately 10 years. CONCLUSION: Overall, feeling lonely is more closely related to Neuroticism than previously understood, and the association endures over time.

Humans↗
PubMed2026

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article↗
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

Shielding performance and clinical applicability of lead-free materials in computed tomography.

Owing to the high radiation exposure associated with computed tomography (CT) examinations and the image quality degradation caused by conventional radiation shielding materials, this study evaluated the dose reduction performance and image quality maintenance potential of a newly developed lead-free composite shielding material. This material was composed of bismuth, tungsten, tungsten carbide, aluminium, and polyurethane. Phantom-based dose measurements demonstrated that the shielding material achieved dose reduction rates ranging from 17.6% to 37.6%, depending on tube voltage. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and changes in tube current-time product (mAs) under a scout-based automatic exposure control (AEC) protocol were analysed according to the presence or absence of the shielding material across regions. For the clinical evaluation, CT scans were performed on four patients. Furthermore, the images were reviewed to evaluate whether this material affected image quality. The shielding material exhibited radiation reduction levels comparable to those reported in previous studies. SNR and CNR analyses showed minor statistical variations in certain regions; however, most differences were not statistically significant, and even significant differences remained within a range that did not compromise diagnostic image quality. Under the scout-based AEC protocol, the use of the shielding material resulted in less than 1% variation in mAs values. No visually perceptible artefacts or clinically significant image quality degradation were observed. The proposed composite shielding material demonstrated the potential to mitigate some limitations of conventional shielding materials and showed preliminary clinical feasibility as an adjunctive strategy for radiation dose reduction in CT examinations.

Radiation Protection↗
PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗
PubMed2026

The voice clone intelligibility benefit in noise in middle-aged listeners.

Research with younger adults showed that cloned voices are more intelligible than human voices in noise, with a benefit of 13.4%. This study tested whether this benefit extends to 40 middle-aged listeners (45-65 years), as this population may show emerging difficulties with speech-in-noise. Participants recognised sentences by ten human voices and ten voice clones in four noise levels. Cloned voices were 11.8% more intelligible, with benefits enhanced at the two most severe noise levels (15.9% at -6 dB and 17.5% at -3 dB), suggesting cloned speech enhanced perception in middle-aged listeners, potentially by reducing listening effort and compensating for emerging age-related auditory-cognitive decline.

Humans↗
PubMed2026

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗
PubMed2026

The cold case of state transition 7 (stt7) mutants of Chlamydomonas reinhardtii, solved by whole-genome sequencing.

The process of State Transitions (ST) corresponds to an STT7 kinase-driven redistribution of the transmembrane LHCII antenna proteins between Photosystem II (PSII) and Photosystem I (PSI), which results from changes in their phosphorylation state. For the past two decades, two LHCII-kinase mutants, stt7-1 and stt7-9, have been instrumental in the study of STs in Chlamydomonas reinhardtii, the former being a null mutant for the kinase but quasi-sterile in crosses, while the latter, although fertile, has a leaky phenotype. Using long-read sequencing, this study further characterized the genetic lesions of the stt7 mutant strains through whole-genome reconstruction and de novo chromosome assembly. In addition, two new stt7 null mutants were generated, one derived by crosses from the original stt7-1 and one obtained by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) technology. This work provides a comprehensive genomic characterization of the original stt7-1 null mutant, revealing extensive chromosomal rearrangements and high levels of aneuploidy, associated with increased cell size and meiotic dysfunction. Reassessment of their physiology and genetic backgrounds highlights the need for caution in interpreting genetic information. We thus produced more reliable null mutants for the LHCII-kinase, amenable to genetic crosses for the study of STs in a variety of genetic backgrounds.

Chlamydomonas reinhardtii↗
PubMed2026

Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of auditory nerve output after threshold recovery.

BACKGROUND: Acoustic stress can alter cochlear function even in the absence of permanent threshold elevation; however, synaptic consequences of transient acoustic stimulation remain incompletely understood. OBJECTIVE: This study aimed to investigate whether transient acoustic stimulation induces changes in the auditory nerve output and cochlear ribbon synapse morphology following hearing threshold recovery. METHODS: Young adult CBA/CaJ mice were exposed to band-limited acoustic stimulation (45-2,000 Hz, 95 dB SPL, 2 h). Auditory brainstem responses (ABRs), hair cell and spiral ganglion neuron survival, and synaptic morphology were evaluated before exposure and up to 2 weeks post-exposure. RESULTS: ABR thresholds were transiently elevated immediately after exposure but largely recovered by 1 day post-exposure. In contrast, ABR wave I amplitudes significantly increased after threshold recovery across multiple test frequencies. Ribbon-associated puncta in both inner and outer hair cell regions exhibited biphasic temporal changes, with an initial decrease immediately after exposure followed by an increase at 1 day post-exposure. The ribbon-associated punctal area also increased after exposure and remained elevated at later post-exposure time points. No significant loss of hair cells or spiral ganglion neurons was observed. Exploratory genomic analysis suggested enrichment of pathways related to metabolic defense and cellular stress responses. CONCLUSIONS: Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of peripheral auditory nerve output without overt cellular degeneration. These findings support a model in which early cochlear responses to acoustic perturbation include adaptive synaptic plasticity and gain regulation, extending current concepts of noise-induced cochlear change beyond irreversible synaptic loss.

Animals↗
PubMed2026

Neuromodulation for Subjective Tinnitus: A Systematic Review and Meta-Analysis of Randomized Trials.

OBJECTIVE: To evaluate the effectiveness and safety of neuromodulation and bimodal stimulation for chronic subjective tinnitus in randomized controlled trials (RCTs). DATA SOURCES: PubMed/MEDLINE, Web of Science, and EMBASE (January 2015-December 2025) searched per PRISMA 2020. REVIEW METHODS: Adult RCTs (≥ 18 years) with chronic subjective tinnitus (> 3 months) assessing validated outcomes (THI, TFI, TQ) for neuromodulation/bimodal interventions vs. sham/controls. Two-stage screening, Cochrane RoB-2 risk-of-bias assessment. Random-effects meta-analyses (REML) were performed when ≥ 3 comparable trials were available; effects reported as standardized mean differences (SMD) with 95% CIs. Main Outcomes and measures included change in tinnitus severity (THI/TFI/TQ) while secondary outcomes included loudness (VAS/NRS), durability, and adverse events. RESULTS: Twenty-six RCTs (n = 1576) met criteria: tES (11; n = 372), rTMS (8; n = 432), acoustic coordinated reset (1; n = 100), vagus nerve stimulation (2; n = 90), and bimodal stimulation (4; n = 582). Meta-analysis showed a nonsignificant pooled effect for tDCS (SMD -0.36; 95% CI -0.75 to 0.02; I 2 = 51%) and rTMS (SMD -0.15; 95% CI -0.37 to 0.07; I 2 = 0%). Single-trial evidence for coordinated reset showed no advantage over broadband noise. VNS demonstrated modest benefits with safety concerns limited to implanted approaches. Bimodal stimulation yielded consistent, clinically meaningful reductions (often ≥ 10-20 points on THI/TFI), with durability up to 12 months. Adverse events were mild/transient across noninvasive modalities. CONCLUSIONS: Noninvasive neuromodulation appears safe with average benefits; among modalities, bimodal stimulation shows the most consistent and durable clinical improvements. Standardized, adequately powered RCTs with harmonized protocols and long-term follow-up are needed to refine targets and dosing.

Humans↗
PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗
PubMed2026

Biliary Cirrhosis in Myhre Syndrome: The First Case Report of Liver Transplantation and a Review of Reported Hepatic Findings.

Myhre syndrome is a rare autosomal-dominant disorder caused by gain-of-function pathogenic variants in SMAD4 and is now recognized as a progressive multisystem fibrotic disease. Although transforming growth factor-β (TGF-β) signaling plays a central role in hepatic fibrogenesis, hepatobiliary involvement in Myhre syndrome has not been systematically evaluated. We report the first case of Myhre syndrome complicated by rapidly progressive biliary cirrhosis requiring liver transplantation in a 15-year-old male with a confirmed SMAD4 p.Ile500Val variant. Following an infectious episode, the patient developed severe cholestasis with imaging and histopathologic findings consistent with fibro-obliterative cholangiopathy, ultimately necessitating living donor liver transplantation. A systematic review of 55 published reports comprising 217 patients with Myhre syndrome revealed that hepatic evaluation was rarely performed and that previously reported liver abnormalities were mild and secondary, most commonly related to right heart dysfunction or metabolic disease, with no prior cases of progressive biliary fibrosis. This case suggests that dysregulated SMAD4-TGF-β signaling may predispose selected organs to fibro-obliterative injury and that infection-driven inflammation may act as a critical trigger for hepatic fibrosis in Myhre syndrome, expanding the recognized spectrum of organ involvement in this disorder.

Humans↗
PubMed2026

Safety and Stability of a Combined C2 Screw Placement Strategy With Vertebral Artery Mobilization.

BACKGROUND: Although C2 pedicle screws are considered the gold standard for atlantoaxial fixation, the optimal fixation strategy for patients with high-riding vertebral arteries (HRVA) or narrow C2 pedicles (NC2P) remains controversial because of the increased risk of vertebral artery injury and the limitations of alternative fixation techniques. OBJECTIVE: To evaluate the safety, stability, and clinical efficacy of an individualized C2 screw fixation strategy incorporating vertebral artery mobilization for complex upper cervical anatomy. METHODS: A retrospective study was conducted in 312 patients who underwent C2 fixation between 2017 and 2025. Patients were categorized according to fusion method, screw laterality, and VA transposition requirement. Bone fusion rates and screw accuracy (Gertzbein-Robbins grading) were compared across groups using &#x3c7;2, Fisher's exact, and multivariate logistic regression analyses to control confounders. RESULTS: All procedures were successfully completed without permanent neurovascular injury. At 6&#x2009;months, the fusion rate with an atlantoaxial fusion cage was significantly higher than with interlaminar bone grafting (92.3% vs. 51.0%, p&#x2009;<&#x2009;0.001). Unilateral C2 pedicle screw fixation combined with a contralateral alternative screw achieved comparable stability to bilateral fixation (p&#x2009;>&#x2009;0.05). Screw placement accuracy was 100% clinically acceptable in normal anatomy and 60% in cases requiring VA mobilization, with no VA injury or blood flow compromise. CONCLUSION: The proposed multi-strategy C2 screw placement protocol-integrating fusion cage support and VA mobilization-achieves superior fusion, reliable fixation, and high safety, even in anatomically challenging conditions. This approach provides a reproducible and versatile solution for C2 instrumentation in complex craniovertebral junction surgery.

Humans↗
PubMed2026

Screening of Estrogenic and Antiestrogenic Effects of Estradiol, Bisphenol A, and Fulvestrant Using 2D and 3D Breast Cancer Cell Systems With a Luciferase Reporter Gene Assay.

Endocrine-disrupting chemicals (EDCs) like bisphenol A (BPA) pose health risks by interfering with hormones. This study develops and utilizes in&#xa0;vitro 2D and 3D cell models to evaluate the estrogenic and antiestrogenic properties of compounds. Human breast cancer cell lines T47D and MCF7, stably transfected with a luciferase reporter gene (ERE-LUC), were first compared in 2D. Due to the significantly higher sensitivity and responsiveness observed in the T47D line during preliminary 2D screenings, this cell line was exclusively selected for the development of the 3D spheroid model. Cells were treated with 17&#x3b2;-estradiol (E2), BPA, and Fulvestrant (FUL) to assess cell viability and luciferase activity. In 2D models, T47D ERE-LUC cells showed higher responsiveness than MCF7 ERE-LUC, which failed to show significant luciferase induction with E2. In the 3D T47D model, cells exhibited significant and robust changes in luciferase activity in response to E2 and BPA, highlighting the enhanced fidelity of 3D cultures in replicating tissue conditions compared to their 2D counterparts. The study highlights the effectiveness of 3D models over 2D in evaluating estrogenic activity. Specifically, the 3D T47D ERE-LUC system serves as a superior, sensitive, and reliable platform for screening EDCs, offering benefits in cost, data speed, and reduced in&#xa0;vivo reliance.

Humans↗
PubMed2026

A First-in-Japanese Phase 1, Double-Blind, Placebo-Controlled, Parallel-Cohort Study of Sefaxersen, an Antisense Oligonucleotide Targeting Complement Factor B, in Healthy Participants.

Increased activity in the complement alternative pathway (AP) plays a key role in diseases such as IgA nephropathy (IgAN). This first-in-Japanese double-blind Phase 1 study investigated the pharmacokinetics (PK), pharmacodynamics (PD), safety, and tolerability of sefaxersen (RO7434656), an antisense oligonucleotide targeting complement factor B messenger RNA. Healthy participants were randomized equally into four cohorts: placebo or sefaxersen 20, 40, or 70&#xa0;mg. The PK, PD, and safety endpoints were monitored throughout the study and during the 90-day follow-up period. All 24 participants completed the study, with no new safety signals or clinically meaningful changes in blood chemistry, electrocardiogram, or vital signs observed. Plasma sefaxersen concentration demonstrated a biphasic PK profile, characterized by an initial rapid decline followed by a slow elimination. Sefaxersen decreased PD markers related to the complement AP selectively, without affecting the classical pathway, in a dose-dependent manner, and the PD effects persisted over 2 to 3 months. Sefaxersen was well tolerated by healthy Japanese participants, with a manageable safety profile. These findings support the inclusion of Japanese patients with IgAN in the global Phase 3 study (IMAGINATION, NCT05797610).

Humans↗
PubMed2026

A cooperative regulatory module between TAGL2 and JMJC1 activates specific defense genes against root-knot nematodes in tomato.

Plant-parasitic nematodes (PPNs) threaten global food security. Although epigenetic modifications are crucial for plant immunity, how histone modifiers contribute to root-knot nematodes (RKNs, Meloidogyne incognita) resistance remains unclear. Here, using genetic, molecular and biochemical approaches, we investigated the epigenetic and transcriptional mechanisms underlying RKN resistance mediated by the histone demethylase (HDM) JMJC1 and the MADS-box transcription factor TAGL2 in tomato (Solanum lycopersicum). We identified JMJC1 as an RKN-induced positive defense regulator targeting H3K9me3 and H3K27me3 histone marks. JMJC1 physically interacts with TAGL2, which also positively regulates RKN resistance. Transcriptomic analysis indicated that TAGL2 regulates multiple layers of the plant defense network, transcriptionally activating representative genes from distinct pathways (including PUB10, bHLH98, CCaMK, and SAUR3), which we validated as positive regulators of RKN resistance via virus-induced gene silencing (VIGS). At the chromatin level, TAGL2 and JMJC1 co-regulate these loci, associating with localized H3K9me3 and H3K27me3 reduction. Furthermore, TAGL2 directly activates JMJC1 transcription, establishing a positive feedback loop that amplifies immune signaling. Our findings reveal a cooperative model wherein a HDM and a transcription factor coordinate at specific loci to fine-tune multiple defense layers at both epigenetic and transcriptional levels, providing insights for breeding durable nematode-resistant plants.

Solanum lycopersicum↗